lib.agents package¶
Submodules¶
lib.agents.Agent_DQN module¶
-
class
lib.agents.Agent_DQN.
Agent_DQN
(env, memory, qNetworkSlow, qNetworkFast, numActions, gamma, device='cpu')[source]¶ Bases:
object
A class allowing the training of the DQN
This class is intended to be used by functions within the
lib.agents.trainAgents
module.The DQN algorithm was first proposed over some years ago and was slated to be used for improving the state of affairs of traditional reinforcement learning and extending it to deep reinforcement learning. This class allows you to easily set up a DQN learning framework. This class does not care about the type of environment. Just that the action an agent is able to take is one of a finite number of actions, each action at a particular state has an associated Q-value. This algorithm attempts to find theright Q value for each action.
The class itself does not care about the specifics of the state, and the Qnetworks that calculate the results. It is up to the user to specify the right environment and the associated networks that will allow the algorithm to solve the Bellman equation.
[link to paper](https://storage.googleapis.com/deepmind-media/dqn/DQNNaturePaper.pdf)
Parameters: - env (instance of an Env class) – The environment that will be used for generating the result of a particulat action in the current state
- memory (instance of the Memory class) – The environment that will allow one to store and retrieve previously held states that can be used to train upon.
- qNetworkSlow (neural network instance) – This is a neural network instance that can be used for converting a state into a set of Q-values. This is the slower version, used for making a prediction, and is never trained. Its parameters are slowly updated over time to slowly allow it to converge to the right value
- qNetworkFast (neural network instance) – This is the instance of the faster network that can be used for training Q-learning algorithm. This is the main network that implements the Bellman equation.
- numActions (int) – The number of discrete actions that the current environment can accept.
- gamma (float) – The discount factor. currently not used
- device (str, optional) – the device where you want to run your algorithm, by default ‘cpu’. If you want to run the optimization of a particular GPU, you may specify that. For example with ‘cuda:0’
Raises: type
– [description]-
checkTrainingMode
()[source]¶ prints whether the networks are in training or eval mode
This function allows us to determine whether the function is in training or evaluation mode. This is important for several things - specifically to make sure that the networks are not going to be randomly evaluated, as well as making sure the things like batch normalization and dropout are properly evaluated.
-
epsGreedyAction
(state, eps=0.999)[source]¶ epsilon greedy action
This is the epsilon greedy action. In general, this is going to select the maximum action
eps
percentage of the times, while selecting the random action the rest of the time. It is assumed that this will receive a value of epsilon between 0 and 1.Parameters: - state ({ndarray}) – [description]
- eps (float, optional) – Determines the fraction of times the max action will be selected in comparison to a random action. (the default is 0.999)
Returns: The 1d tensor that has an action for each state provided.
Return type: tensor
-
eval
()[source]¶ put both the networks in eval mode
This will allow us to make sure that the networks do not randomly get evaluated for some reason.
-
fastUpdate
(tau=1)[source]¶ update the fast network slightly
This is going to update the fast network slightly. The amount is dictated by
tau
. This should be a number between 0 and 1. It will update thetau
fraction of the slow network weights with the new weights. This is done for providing stability to the network.Parameters: tau ({number}, optional) – This parameter determines how much of the slow Networks weights will be updated to the fast parameters weights (the default is 1)
-
load
(folder, name, map_location=None)[source]¶ load the model
An agent saved with the save command can be safely loaded with this command. This will load both the qNetworks, as well as the memory buffer. There is a possibility that one may not want to load the model into the same device. In that case, the user should insert the device that the user wants to load the model into.
Parameters: - folder ({str}) – folder into which the model should be saved.
- name ({str}) – A name to associate the model to load. It is absolutelty possible to save a number of models within the same folder, and hence the name can retrieve that model that is important.
- map_location ({str}, optional) – The device in which to load the file. This is a string like ‘cpu’, ‘cuad:0’ etc. (the default is None, which results in the model being loaded to the originam device)
-
maxAction
(state)[source]¶ returns the action that maximizes the Q function
Given an set of statees, this function is going to return a set of actions which will maximize the value of the Q network for each of the supplied states.
Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return values of actions that maximize the states Return type: uarray
-
memoryUpdateEpisode
(policy, maxSteps=1000, minScoreToAdd=None)[source]¶ update the memory
Given a particular policy, this memory is going to take the policy and generate a series of memories and update thememory buffer. Generating memories is easier to do using this function than an external function …
Parameters: - policy ({function}) – This is a function that takes a state and returns an action. This defines how the agent will explore the environment by changing the exploration/exploitation scale.
- maxSteps ({number}, optional) – The maximum number of steps that one shoule have within an episode. (the default is 1000)
-
randomAction
(state)[source]¶ returns a set of random actions for the given states
given the size of the number of actions, this function is going to return a set of actions that has the same number of actions as the number of inputs in the shape. For example, if
state.shape == (10, ?)
then the result will be a vector of size 10. This is in accordance with the redduction in the dimensionality of the maxAction space.Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return value is set of random actions Return type: uarray
-
save
(folder, name)[source]¶ save the model
This function allows one to save the model, in a folder that is specified, with the fast and the slow qNetworks, as well as the memory buffer. Sometimes there may be more than a single agent, and under those circumstances, the name will come in handy. If the supplied folder does not exist, it will be generated.
Parameters: - folder ({str}) – folder into which the model should be saved.
- name ({str}) – A name to associate the current model with. It is absolutelty possible to save a number of models within the same folder.
-
sigmaMaxAction
(state, sigma=0)[source]¶ returns the action that maximizes the noisy Q function
Given an set of statees, this function is going to return a set of actions which will maximize the value of the Q network for each of the supplied states, after adding Gaussian noise to the layers. This is alternative to using an $epsilon$-greedy policy, and has shown to provide better results under most circumstances.
Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return values of actions that maximize the states Return type: uarray
-
softUpdate
(tau=0.1)[source]¶ update the slow network slightly
This is going to update the slow network slightly. The amount is dictated by
tau
. This should be a number between 0 and 1. It will update thetau
fraction of the slow network weights with the new weights. This is done for providing stability to the network.Parameters: tau ({number}, optional) – This parameter determines how much of the fast Networks weights will be updated to the ne parameters weights (the default is 0.1)
-
step
(nSamples=100, sigma=0)[source]¶ optimize the fast Q network via the bellman equations
This function is going to obtain a number of samples form the replay memory, and train the fast network over this dataset. This will optimize based upon the idea that
> Given: > Qf = fast network > Qs = slow network > s = current state > a = action that maximizes the current state > r = reward > s’ = next state > > Qf(s, a) = r + max(Qs(s’))
Parameters: - nSamples (int, optional) – The number of samples too retrieve from the replay memory for training, by default 100
- sigma (float, optional) – The amount by which the fast network should be jittered so that the network introduces some Gaussian noise in the learning process, by default 0, which does not introduce noise in the learning algorithm.
Raises: type
– [description]
lib.agents.Agent_DoubleDQN module¶
-
class
lib.agents.Agent_DoubleDQN.
Agent_DoubleDQN
(env, memory, qNetworkSlow, qNetworkFast, numActions, gamma, device='cpu')[source]¶ Bases:
object
A class allowing the training of the DQN
This class is intended to be used by functions within the
lib.agents.trainAgents
module.This is supposed to be an imporvement over DQN. Details of the idea behind Double DQN is present in the original paper:
Deep Reinforcement Learning with Double Q-learning https://arxiv.org/pdf/1509.06461.pdf
See the
step()
function for the details of its implementation.Parameters: - env (instance of an Env class) – The environment that will be used for generating the result of a particulat action in the current state
- memory (instance of the Memory class) – The environment that will allow one to store and retrieve previously held states that can be used to train upon.
- qNetworkSlow (neural network instance) – This is a neural network instance that can be used for converting a state into a set of Q-values. This is the slower version, used for making a prediction, and is never trained. Its parameters are slowly updated over time to slowly allow it to converge to the right value
- qNetworkFast (neural network instance) – This is the instance of the faster network that can be used for training Q-learning algorithm. This is the main network that implements the Bellman equation.
- numActions (int) – The number of discrete actions that the current environment can accept.
- gamma (float) – The discount factor. currently not used
- device (str, optional) – the device where you want to run your algorithm, by default ‘cpu’. If you want to run the optimization of a particular GPU, you may specify that. For example with ‘cuda:0’
Raises: type
– [description]-
checkTrainingMode
()[source]¶ prints whether the networks are in training or eval mode
This function allows us to determine whether the function is in training or evaluation mode. This is important for several things - specifically to make sure that the networks are not going to be randomly evaluated, as well as making sure the things like batch normalization and dropout are properly evaluated.
-
epsGreedyAction
(state, eps=0.999)[source]¶ epsilon greedy action
This is the epsilon greedy action. In general, this is going to select the maximum action
eps
percentage of the times, while selecting the random action the rest of the time. It is assumed that this will receive a value of epsilon between 0 and 1.Parameters: - state ({ndarray}) – [description]
- eps (float, optional) – Determines the fraction of times the max action will be selected in comparison to a random action. (the default is 0.999)
Returns: The 1d tensor that has an action for each state provided.
Return type: tensor
-
eval
()[source]¶ put both the networks in eval mode
This will allow us to make sure that the networks do not randomly get evaluated for some reason.
-
fastUpdate
(tau=1)[source]¶ update the fast network slightly
This is going to update the fast network slightly. The amount is dictated by
tau
. This should be a number between 0 and 1. It will update thetau
fraction of the slow network weights with the new weights. This is done for providing stability to the network.Parameters: tau ({number}, optional) – This parameter determines how much of the slow Networks weights will be updated to the fast parameters weights (the default is 1)
-
load
(folder, name, map_location=None)[source]¶ load the model
An agent saved with the save command can be safely loaded with this command. This will load both the qNetworks, as well as the memory buffer. There is a possibility that one may not want to load the model into the same device. In that case, the user should insert the device that the user wants to load the model into.
Parameters: - folder ({str}) – folder into which the model should be saved.
- name ({str}) – A name to associate the model to load. It is absolutelty possible to save a number of models within the same folder, and hence the name can retrieve that model that is important.
- map_location ({str}, optional) – The device in which to load the file. This is a string like ‘cpu’, ‘cuad:0’ etc. (the default is None, which results in the model being loaded to the originam device)
-
maxAction
(state)[source]¶ returns the action that maximizes the Q function
Given an set of statees, this function is going to return a set of actions which will maximize the value of the Q network for each of the supplied states.
Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return values of actions that maximize the states Return type: uarray
-
memoryUpdateEpisode
(policy, maxSteps=1000, minScoreToAdd=None)[source]¶ update the memory
Given a particular policy, this memory is going to take the policy and generate a series of memories and update thememory buffer. Generating memories is easier to do using this function than an external function …
Parameters: - policy ({function}) – This is a function that takes a state and returns an action. This defines how the agent will explore the environment by changing the exploration/exploitation scale.
- maxSteps ({number}, optional) – The maximum number of steps that one shoule have within an episode. (the default is 1000)
-
randomAction
(state)[source]¶ returns a set of random actions for the given states
given the size of the number of actions, this function is going to return a set of actions that has the same number of actions as the number of inputs in the shape. For example, if
state.shape == (10, ?)
then the result will be a vector of size 10. This is in accordance with the redduction in the dimensionality of the maxAction space.Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return value is set of random actions Return type: uarray
-
save
(folder, name)[source]¶ save the model
This function allows one to save the model, in a folder that is specified, with the fast and the slow qNetworks, as well as the memory buffer. Sometimes there may be more than a single agent, and under those circumstances, the name will come in handy. If the supplied folder does not exist, it will be generated.
Parameters: - folder ({str}) – folder into which the model should be saved.
- name ({str}) – A name to associate the current model with. It is absolutelty possible to save a number of models within the same folder.
-
sigmaMaxAction
(state, sigma=0)[source]¶ returns the action that maximizes the noisy Q function
Given an set of statees, this function is going to return a set of actions which will maximize the value of the Q network for each of the supplied states, after adding Gaussian noise to the layers. This is alternative to using an $epsilon$-greedy policy, and has shown to provide better results under most circumstances.
Parameters: state ({nd_array or tensor}) – numpy array or tensor containing the state. The columns represent the different parts of the state. Returns: The return values of actions that maximize the states Return type: uarray
-
softUpdate
(tau=0.1)[source]¶ update the slow network slightly
This is going to update the slow network slightly. The amount is dictated by
tau
. This should be a number between 0 and 1. It will update thetau
fraction of the slow network weights with the new weights. This is done for providing stability to the network.Parameters: tau ({number}, optional) – This parameter determines how much of the fast Networks weights will be updated to the ne parameters weights (the default is 0.1)
-
step
(nSamples=100, sigma=0)[source]¶ optimize the fast Q network via the bellman equations
This function is going to obtain a number of samples form the replay memory, and train the fast network over this dataset. The idea behind this is that the Q network for the next step will not automatically pick the next best value. It will possibly pick the best value that the Fast network thinks it will pick, and so the original DQN will overestimate the possible Q value. This should reduce that estimation.
This will optimize based upon the idea that
> Given: > Qf = fast network > Qs = slow network > s = current state > a = action that maximizes the current state > r = reward > s’ = next state > > a’ = argmax Qf(s’) > Qf(s, a) = r + Qs(s’, a’)
Parameters: - nSamples (int, optional) – The number of samples too retrieve from the replay memory for training, by default 100
- sigma (float, optional) – The amount by which the fast network should be jittered so that the network introduces some Gaussian noise in the learning process, by default 0, which does not introduce noise in the learning algorithm.
Raises: type
– [description]
lib.agents.policy module¶
lib.agents.qNetwork module¶
-
class
lib.agents.qNetwork.
qNetworkDiscrete
(stateSize, actionSize, layers=[10, 5], activations=[<function tanh>, <function tanh>], batchNormalization=False, lr=0.01)[source]¶ Bases:
torch.nn.modules.module.Module
This is a Q network with discrete actions
This takes a state and returns a Q function for each action. Hence, the input is a state and the output is a set of Q values, one for each action in the action space. The action is assumed to be discrete. i.e. a
1
when the particular action is to be desired. The input state is assumed to be 1D in nature. A different network will have to be chosen if 2D and 3D inputs are to be desired.Parameters: - stateSize ({int}) – Size of the state. Since this is a 1D network, this represents the number of values will be used to represent the current state.
- actionSize ({int}) – The number of discrete actions that will be used.
- layers ({list of int}, optional) – The number of nodes associated with each layer (the default is
[10, 5]
, which will create two hidden layers with and and 5 nodes each) - activations ({list of activations}, optional) – The activation functions to be used for each layer (the default is
[F.tanh, F.tanh]
, which will generate tanh activations for each of the hidden layers) - batchNormalization ({bool}, optional) – Whether batchnormalization is to be used (the default is
False
, for which batch normalization will be neglected)
-
forward
(x, sigma=0)[source]¶ forward function that is called during the forward pass
This is the forward function that will be called during a forward pass. It takes thee states and gives the Q value correspondidng to each of the applied actions that are associated with that state.
Parameters: x (Tensor) – This is a 2D tensor. Returns: This represents the Q value of the function Return type: tensor
-
step
(v1, v2)[source]¶ Uses the optimizer to update the weights
This calculates the MSE loss given two inputs, one of which must be calculated with this current
nn.Module
, and the other one that is expected.Note that this allows arbitrary functions to be used for calculating the loss.
Parameters: - v1 ({Tensor}) – Tensor for calculating the loss function
- v2 ({Tensor}) – Tensor for calculating the loss function
Raises: type
– [description]
lib.agents.randomActor module¶
-
class
lib.agents.randomActor.
randomDiscreteActor
(stateShape, numActions)[source]¶ Bases:
object
a random discrete actor
A discrete action space is one where the actor will return an integer which will represent one of n actions. This actor will return a random action independent of the state the environment is in. This will be roughly uniformly distributed.
Parameters: - {tuple} -- Tuple of integers that will describe (stateShape) – the dimensions of the state space
- {integer} -- An action that the agent will do. (numActions) –
lib.agents.sequentialActor module¶
-
class
lib.agents.sequentialActor.
SequentialDiscreteActor
(stateSize, numActions, layers=[10, 5], activations=[<function tanh>, <function tanh>], batchNormalization=True)[source]¶ Bases:
torch.nn.modules.module.Module
[summary]
[description]
Parameters: - {[type]} -- [description] (numActions) –
- {[type]} -- [description] –
Keyword Arguments: - {list} -- [description] (default (activations) – {[10, 5]})
- {list} -- [description] (default – {[F.tanh, F.tanh]})
- {bool} -- [description] (default (batchNormalization) – {True})
-
forward
(x)[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
lib.agents.sequentialCritic module¶
-
class
lib.agents.sequentialCritic.
SequentialCritic
(stateSize, actionSize, layers=[10, 5], activations=[<function tanh>, <function tanh>], mergeLayer=0, batchNormalization=True)[source]¶ Bases:
torch.nn.modules.module.Module
[summary]
[description]
Parameters: - stateSize ({[type]}) – [description]
- actionSize ({[type]}) – [description]
- layers ({list}, optional) – [description] (the default is [10, 5], which [default_description])
- activations ({list}, optional) – [description] (the default is [F.tanh, F.tanh], which [default_description])
- batchNormalization ({bool}, optional) – [description] (the default is True, which [default_description])
-
forward
(x, action)[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
Module contents¶
module that contains a plethora of agents and policies
This module will contain a number of agents and policies that can be specified by easily in a uniform manner. This way different agents can be easily swapped out between each other.
Agents¶
Agents take a state and return an action. Unfortunately, both states and actions come in a variety of shapes and sizes.
There are essentially two different types of states. Either a vector, or an nd-array. Typically, nd-arrays are dealt with coonvolution operators whiile vectors are dealt with simple sequential networks. While nd-arrays can be flattened, the reverse operator us generally not practicable. In any case, it is assumed that the user has enough intuition to be able to distinguish between the two.
Actions are typically vectors. However, sometimes actions can be discrete and sometimes contnuous and any combination of the two. Furthermore, actions typically have bounds. In more general cases (like chess) valid actions are associated with the current state. There is no generic way of solving this problem, so we chall create different types of agents that will return different types of actions.
All agets will definitely have the following methods:
act
: action to take given a statesave
: save the current state of the agentrestore
: restore the agent from a state saved earlier
Currently the following agents are available:
Policies¶
Policies determine what action to take given the result of an agent. In one way, they are similar in that they also take a state, and return an action. However, a policy determines how much exploration vs. exploitation should be done over the period that the agent is learning.


Introduction
This document provides instructions on how to locate the Stan code
for the models used in the publication:
Dynamics of gut mucosal colonisation with extended spectrum
beta-lactamase producing Enterobacterales in Malawi
Joseph M Lewis1,2,3,4, , Madalitso Mphasa1,
Rachel Banda1, Matthew Beale4, Eva
Heinz2, Jane Mallewa5, Christopher
Jewell6, Nicholas R Thomson4, Nicholas A
Feasey1,2
- Malawi Liverpool Wellcome Clinical Research Programme, Blantyre,
Malawi
- Liverpool School of Tropical Medicine, Liverpool, UK
- Department of Clinical Infection, Microbiology and Immunology,
University of Liverpool, Liverpool, UK
- Wellcome Sanger Institute, Hinxton, UK
- College of Medicine, University of Malawi, Malawi
- University of Lancaster, Lanaster, UK
- London School of Tropical Medicine and Hygiene, London, UK
Locating Stan code
The stan model has the filename
ESBLmod_finalV1.0_rk45.stan
are present in the `extdata/
directory of the installed package, which can be located with the
following command:
system.file("extdata",
"ESBLmod_finalV1.0_rk45.stan",
package = "blantyreESBL")
#> [1] "/private/var/folders/qc/twvrz5kx0gj2lrt4n8wtk1ym0000gn/T/Rtmpb1nkZ6/temp_libpath106dc71bfd600/blantyreESBL/extdata/ESBLmod_finalV1.0_rk45.stan"
Model specification
The model can include covariates that are:
- Non time varying
- Time varying with stepwise constant effect (equivalent to the models
fitted by the R package msm)
- Time varying with exponential decay following exposure
See the manuscript for details
Passing data to the model
The model expects the following data as input; each item is passed as
a named item in a list to the rstan stan
command to fit the
model. Each
- N [integer]
- Number of rows of data, each row consisting of two ESBL observations
separated by a time t for one patient. Each patient can have multiple
rows of data.
- n_covs [integer vector of length 3]
- This specifies the number of covariates to be fitted in the
model.
- It should be formatted: [number of nontimevarying covariates, number
of stepwise constant covariates, number of exp decay covariates ]
- covs_type [integer vector of length(number of covariates)]
- Each position encodes the type of variable in the order they are
presented in covs_mat (all the exp decay variables must always go
first):
- 3 = time varying with exponential decay of effect
- 2 = time varying with piecewise constant
- 1 = non time varying
- t [integer vector of length N]
- Time separating beginning and end ESBL observations for each row of
data
- cov_mat [real matrix with 3*(number of covariate) columns and N
rows]
- Start and stop times of covariates, ordered as per covs_type
- Each covariate needs three columns, in this order
- start_time: time that covariate exposure started
- if there is no exposure in this row, code as -999
- stop time: time that covariate exposure stopped
- if there is no exposure in this row, code as -999
- prev_stop time:
- if covariate has exp. decay, this is the previous stop time (before
current row e.g. -10 for 10 days ago)
- If no previous exposure, code as 999
- If non time varying exposure, code as 999 = present, -999
absent
- start state [ matrix with N rows and two columns ]
- each row is start state for that time period in format (ESBL-,
ESBL+) ie esbl positive coded as [0,1] and ESBL negative coded as
[1,0]
- end state: [integer]
- final state; ESBL+ = 1, ESBL- = 0
The included data btESBL_stanmodeldata
is set up to fit
the model used in the manuscript.
Fitting the model
The following code (not run in this vignette) will fit the model as
in the manuscript:
library(rstan)
library(blantyreESBL)
stan(
file = system.file("extdata",
"ESBLmod_finalV1.0_rk45.stan",
package = "blantyreESBL")
data = btESBL_stanmodeldata,
warmup = 500,
iter = 1000,
chains = 4
) -> stanfit
Simulating from the model
The script simulate_from_posterior.R
will generate the
simulations used in the analysis. It is included in the package install
and again can be located by:
system.file("extdata",
"simulate_from_posterior.R",
package = "blantyreESBL")
#> [1] "/private/var/folders/qc/twvrz5kx0gj2lrt4n8wtk1ym0000gn/T/Rtmpb1nkZ6/temp_libpath106dc71bfd600/blantyreESBL/extdata/simulate_from_posterior.R"
Or it is located (along withe stan model) in the
inst/extdata/
folder on the github repo.


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Multigraph Timestamps Wrong |
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50 weeks 23 hours ago by Esk Energy |
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ERROR: Feed could not be created, undefined |
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n/a |
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Configure input for external data |
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redis enabled but not installed *solved |
0 |
51 weeks 1 day ago by MrGlasspoole |
n/a |
|
|
min/max feeds not working at emoncms.org |
9 |
51 weeks 2 days ago by nilrog |
50 weeks 6 days ago by nilrog |
|
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EmonCMS Configure Visualisation Header Improvement |
0 |
51 weeks 3 days ago by nuno |
n/a |
|
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emonhub.service failed to load: No such file or directory |
0 |
51 weeks 3 days ago by MrGlasspoole |
n/a |
|
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Virtual Feeds treat 0 as missing |
0 |
51 weeks 3 days ago by Esk Energy |
n/a |
|
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emoncms.org: incorrect kWh data |
32 |
51 weeks 3 days ago by TrystanLea |
47 weeks 4 days ago by blasco73 |
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|
emonpi avrdude update failure - sync |
5 |
51 weeks 3 days ago by fubar |
51 weeks 3 days ago by Robert Wall |
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MQTT Duplicate Inputs created after several reboots |
15 |
51 weeks 3 days ago by sheppy |
50 weeks 5 days ago by Paul Reed |
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Memcached - installation problems. |
0 |
51 weeks 3 days ago by MrGlasspoole |
n/a |
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CSV Export phptimeseries wrong values? |
0 |
51 weeks 3 days ago by Esk Energy |
n/a |
|
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Full API documentation? |
2 |
51 weeks 4 days ago by ChrisValentine |
51 weeks 2 hours ago by ChrisValentine |
|
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Emoncms.org service outage 25th Feb |
15 |
51 weeks 4 days ago by TrystanLea |
47 weeks 6 days ago by andrea.rimo |
|
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Why MySQL and HTTP-Requests? |
10 |
51 weeks 4 days ago by MrGlasspoole |
51 weeks 2 days ago by MrGlasspoole |
|
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Emoncms.org data updating very infrequently |
8 |
51 weeks 4 days ago by webby |
51 weeks 4 days ago by TrystanLea |
|
|
Dashboard faults |
4 |
51 weeks 4 days ago by Fwerryb4 |
51 weeks 2 days ago by Fwerryb4 |
|
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Emoncms.org service outage |
1 |
51 weeks 6 days ago by TrystanLea |
51 weeks 5 days ago by TrystanLea |
|
|
Is faster sampling firmware practicable? |
8 |
51 weeks 6 days ago by fubar |
50 weeks 5 days ago by fubar |
|
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python code to parse emonhub v8.5 raw php data files available for anyone who cares.. |
3 |
52 weeks 12 hours ago by fubar |
51 weeks 4 days ago by fubar |
|
|
(Release Candidate #1 ): emonSD-20Feb16 - emonPi / emonBase (Raspberry Pi + RFM69Pi) Emoncms v9 pre-built SD card image |
75 |
1 year 1 hour ago by glyn.hudson |
43 weeks 2 hours ago by glyn.hudson |
|
|
Feeds not updating - PHPFina:post timestamp out of range |
6 |
1 year 16 hours ago by dthp |
52 weeks 22 hours ago by dthp |
|
|
Victron Energy protocol integration with emonhub |
2 |
1 year 2 days ago by atilev |
50 weeks 4 days ago by atilev |
|
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mysolar will not work with Read API key? |
2 |
1 year 2 days ago by Peter Galbavy |
1 year 2 days ago by Peter Galbavy |
|
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Rounding on large incrementing counter values |
11 |
1 year 3 days ago by a234525 |
50 weeks 5 days ago by Eric_AMANN |
|
|
Problem with email at emoncms event |
2 |
1 year 3 days ago by Langeb2000 |
51 weeks 6 days ago by pb66 |
|
|
(BETA #2): emonSD-16Feb16 - emonPi / emonBase (Raspberry Pi + RFM69Pi) Emoncms v9 pre-built SD card image |
15 |
1 year 4 days ago by glyn.hudson |
1 year 35 min ago by glyn.hudson |
|
|
"emonRX" with RFM12 and 4-line i2c LCD |
7 |
1 year 4 days ago by qabo0101 |
51 weeks 4 days ago by qabo0101 |
|
|
Cannot send data while viewing on same network |
4 |
1 year 5 days ago by Steven7007 |
1 year 3 days ago by remet |
|
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Error: connect ETIMEDOUT in Nodered |
1 |
1 year 5 days ago by cormad |
1 year 3 days ago by jvda |
|
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Using EmonLib.h library |
4 |
1 year 6 days ago by FutureEngineer |
1 year 5 days ago by Robert Wall |
|
|
My Electric, 9.31 |
0 |
1 year 6 days ago by sumo |
n/a |
|
|
Getting data from Blueline Wifi Powercost monitor into EmonCMS |
4 |
1 year 1 week ago by mattncsu |
1 year 1 week ago by mattncsu |
|
|
emonhub: "Device communication error - check settings" |
3 |
1 year 1 week ago by jvda |
1 year 1 week ago by jvda |
|
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Low-power sketch for reed switch pulse counting on EmonTH |
14 |
1 year 1 week ago by Eric_AMANN |
50 weeks 2 days ago by glyn.hudson |
|
|
(ALPHA): LATEST emonSD12Feb16 - emonPi / emonBase (Raspberry Pi + RFM69Pi) Emoncms v9 pre-built SD card image |
46 |
1 year 1 week ago by glyn.hudson |
1 year 4 days ago by jason |
|
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Using reporter to Emoncms.org with emoncms on linux hosting |
2 |
1 year 1 week ago by Roeland54 |
1 year 1 week ago by Roeland54 |
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Are there any Arduino SD shield Data Logging scripts available? |
1 |
1 year 1 week ago by energyguy |
1 year 1 week ago by Robert Wall |


Example AMD use of the Promiseifyish library
require
:
require(
// The path to the Promiseifyish.js file
['../../scripts/Promiseifyish.js'],
// A callback which is executed with the Promiseifyish instance
function onLoaded(Promiseifyish) {
/* code here */
}
);
| Method | Result |
|---|---|
| Standard |
|
| Promiseified |
|


About
alex horton
Work
I'm a developer who's passionate about making stuff.
And jorts.
What matters to me
Clean and simple aesthetics
Well-designed solutions to problems
Being a good teammate
Growth
My wife and dogs
Bourbon
Work


{* use %s in subject to insert vacancy title *}
[t]Dear[/t] {$candidateName|escape}[t],[/t]
[t]A new job opportunity has been created by[/t] {$clientName|escape} [t]with the job title[/t] {$vacancyTitle|escape} [t]and the following details:[/t]
{$vacancyDescription}
[t]Click on the link below if you are interested in the job:[/t]
{$urlDescription|escape}
[t]Regards,[/t]
{$userName}
{$clientName}
{$userSignature}
{/if}


new CanvasPool() The CanvasPool is a global static object that allows Pixi and Phaser to pool canvas DOM elements. Source - pixi/utils/CanvasPool.js, line 7 Members <static> pool :Array The pool into which the canvas dom elements are placed. Source - pixi/utils/CanvasPool.js, line 173 Methods <static> create(parent, width, height) ? {HTMLCanvasElement} Creates a new Canvas DOM element, or pulls one from the pool if free. Parameters: Name Type Description parent The parent of the canvas element. width Number The width of the canvas element. height Number The height of the canvas element. Returns: HTMLCanvasElement - The canvas element. Source - pixi/utils/CanvasPool.js, line 15 <static> getFirst() ? {Number} Gets the first free canvas index from the pool. Returns: Number - Source - pixi/utils/CanvasPool.js, line 58 <static> getFree() ? {Number} Gets the total number of free canvas elements in the pool. Returns: Number - The number of free (un-parented) canvas elements in the pool. Source - pixi/utils/CanvasPool.js, line 147 <static> getTotal() ? {Number} Gets the total number of used canvas elements in the pool. Returns: Number - The number of in-use (parented) canvas elements in the pool. Source - pixi/utils/CanvasPool.js, line 123 <static> remove(parent) Removes the parent from a canvas element from the pool, freeing it up for re-use. Parameters: Name Type Description parent The parent of the canvas element. Source - pixi/utils/CanvasPool.js, line 81 <static> removeByCanvas(canvas) Removes the parent from a canvas element from the pool, freeing it up for re-use. Parameters: Name Type Description canvas HTMLCanvasElement The canvas element to remove Source - pixi/utils/CanvasPool.js, line 102


{% extends 'base.html' %} {% block content%} {% load static %} Financini ? Financini is a credit scoring platform not only built to speed up the long traditional process and save your time also because we respect your future projects Get Started {% endblock %}
Financini is a credit scoring platform not only built to speed up the long traditional process and save your time also because we respect your future projects


Hello again! Welcome to the Dragon Wiki- the Dragon Ball Wikipedia.
This is a collection of various Dragon Ball characters, with details about them.
This is an application built to teach you how you can play with PHP and HTML to create web-apps you like.
I hope you will enjoy.
Lets get in!.


metricbeat.reference.ymledit
The following reference file is available with your Metricbeat installation. It
shows all non-deprecated Metricbeat options. You can copy from this file and paste
configurations into the metricbeat.yml
file to customize it.
For rpm and deb, you’ll find the reference configuration file at /etc/metricbeat/metricbeat.reference.yml
. Under
Docker, it’s located at /usr/share/metricbeat/metricbeat.reference.yml
. For mac and win,
look in the archive that you just extracted.
The contents of the file are included here for your convenience.
########################## Metricbeat Configuration ########################### # This file is a full configuration example documenting all non-deprecated # options in comments. For a shorter configuration example, that contains only # the most common options, please see metricbeat.yml in the same directory. # # You can find the full configuration reference here: # https://www.elastic.co/guide/en/beats/metricbeat/index.html #============================ Config Reloading =============================== # Config reloading allows to dynamically load modules. Each file which is # monitored must contain one or multiple modules as a list. metricbeat.config.modules: # Glob pattern for configuration reloading path: ${path.config}/conf.d/*.yml # Period on which files under path should be checked for changes reload.period: 10s # Set to true to enable config reloading reload.enabled: false # Maximum amount of time to randomly delay the start of a metricset. Use 0 to # disable startup delay. metricbeat.max_start_delay: 10s #============================== Autodiscover =================================== # Autodiscover allows you to detect changes in the system and spawn new modules # as they happen. #metricbeat.autodiscover: # List of enabled autodiscover providers # providers: # - type: docker # templates: # - condition: # equals.docker.container.image: etcd # config: # - module: etcd # metricsets: ["leader", "self", "store"] # period: 10s # hosts: ["${host}:2379"] #========================== Modules configuration ============================ metricbeat.modules: #------------------------------- System Module ------------------------------- - module: system metricsets: - cpu # CPU usage - load # CPU load averages - memory # Memory usage - network # Network IO - process # Per process metrics - process_summary # Process summary - uptime # System Uptime #- core # Per CPU core usage #- diskio # Disk IO #- filesystem # File system usage for each mountpoint #- fsstat # File system summary metrics #- raid # Raid #- socket # Sockets and connection info (linux only) enabled: true period: 10s processes: ['.*'] # Configure the metric types that are included by these metricsets. cpu.metrics: ["percentages"] # The other available options are normalized_percentages and ticks. core.metrics: ["percentages"] # The other available option is ticks. # A list of filesystem types to ignore. The filesystem metricset will not # collect data from filesystems matching any of the specified types, and # fsstats will not include data from these filesystems in its summary stats. # If not set, types associated to virtual filesystems are automatically # added when this information is available in the system (e.g. the list of # `nodev` types in `/proc/filesystem`). #filesystem.ignore_types: [] # These options allow you to filter out all processes that are not # in the top N by CPU or memory, in order to reduce the number of documents created. # If both the `by_cpu` and `by_memory` options are used, the union of the two sets # is included. #process.include_top_n: # Set to false to disable this feature and include all processes #enabled: true # How many processes to include from the top by CPU. The processes are sorted # by the `system.process.cpu.total.pct` field. #by_cpu: 0 # How many processes to include from the top by memory. The processes are sorted # by the `system.process.memory.rss.bytes` field. #by_memory: 0 # If false, cmdline of a process is not cached. #process.cmdline.cache.enabled: true # Enable collection of cgroup metrics from processes on Linux. #process.cgroups.enabled: true # A list of regular expressions used to whitelist environment variables # reported with the process metricset's events. Defaults to empty. #process.env.whitelist: [] # Include the cumulative CPU tick values with the process metrics. Defaults # to false. #process.include_cpu_ticks: false # Raid mount point to monitor #raid.mount_point: '/' # Configure reverse DNS lookup on remote IP addresses in the socket metricset. #socket.reverse_lookup.enabled: false #socket.reverse_lookup.success_ttl: 60s #socket.reverse_lookup.failure_ttl: 60s # Diskio configurations #diskio.include_devices: [] #------------------------------ Aerospike Module ----------------------------- - module: aerospike metricsets: ["namespace"] enabled: true period: 10s hosts: ["localhost:3000"] #------------------------------- Apache Module ------------------------------- - module: apache metricsets: ["status"] period: 10s enabled: true # Apache hosts hosts: ["http://<IP_ADDRESS>"] # Path to server status. Default server-status #server_status_path: "server-status" # Username of hosts. Empty by default #username: username # Password of hosts. Empty by default #password: password #-------------------------------- Ceph Module -------------------------------- - module: ceph metricsets: ["cluster_disk", "cluster_health", "monitor_health", "pool_disk", "osd_tree"] period: 10s hosts: ["localhost:5000"] enabled: true #------------------------------ Couchbase Module ----------------------------- - module: couchbase metricsets: ["bucket", "cluster", "node"] period: 10s hosts: ["localhost:8091"] enabled: true #------------------------------- Docker Module ------------------------------- - module: docker metricsets: - "container" - "cpu" - "diskio" - "healthcheck" - "info" #- "image" - "memory" - "network" hosts: ["unix:///var/run/docker.sock"] period: 10s enabled: true # If set to true, replace dots in labels with `_`. #labels.dedot: false # To connect to Docker over TLS you must specify a client and CA certificate. #ssl: #certificate_authority: "/etc/pki/root/ca.pem" #certificate: "/etc/pki/client/cert.pem" #key: "/etc/pki/client/cert.key" #----------------------------- Dropwizard Module ----------------------------- - module: dropwizard metricsets: ["collector"] period: 10s hosts: ["localhost:8080"] metrics_path: /metrics/metrics namespace: example enabled: true #---------------------------- Elasticsearch Module --------------------------- - module: elasticsearch metricsets: - node - node_stats #- index #- index_recovery #- index_summary #- shard #- ml_job period: 10s hosts: ["localhost:9200"] #username: "elastic" #password: "changeme" #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Set to false to fetch all entries #index_recovery.active_only: true #----------------------------- envoyproxy Module ----------------------------- - module: envoyproxy metricsets: ["server"] period: 10s hosts: ["localhost:9901"] #-------------------------------- Etcd Module -------------------------------- - module: etcd metricsets: ["leader", "self", "store"] period: 10s hosts: ["localhost:2379"] #------------------------------- Golang Module ------------------------------- - module: golang #metricsets: # - expvar # - heap period: 10s hosts: ["localhost:6060"] heap.path: "/debug/vars" expvar: namespace: "example" path: "/debug/vars" #------------------------------ Graphite Module ------------------------------ - module: graphite metricsets: ["server"] enabled: true # Host address to listen on. Default localhost. #host: localhost # Listening port. Default 2003. #port: 2003 # Protocol to listen on. This can be udp or tcp. Default udp. #protocol: "udp" # Receive buffer size in bytes #receive_buffer_size: 1024 #templates: # - filter: "test.*.bash.*" # This would match metrics like test.localhost.bash.stats # namespace: "test" # template: ".host.shell.metric*" # test.localhost.bash.stats would become metric=stats and tags host=localhost,shell=bash # delimiter: "_" #------------------------------- HAProxy Module ------------------------------ - module: haproxy metricsets: ["info", "stat"] period: 10s hosts: ["tcp://<IP_ADDRESS>:14567"] enabled: true #-------------------------------- HTTP Module -------------------------------- - module: http #metricsets: # - json period: 10s hosts: ["localhost:80"] namespace: "json_namespace" path: "/" #body: "" #method: "GET" #username: "user" #password: "secret" #request.enabled: false #response.enabled: false #json.is_array: false #dedot.enabled: false - module: http #metricsets: # - server host: "localhost" port: "8080" enabled: false #paths: # - path: "/foo" # namespace: "foo" # fields: # added to the the response in root. overwrites existing fields # key: "value" #------------------------------- Jolokia Module ------------------------------ - module: jolokia #metricsets: ["jmx"] period: 10s hosts: ["localhost"] namespace: "metrics" #path: "/jolokia/?ignoreErrors=true&canonicalNaming=false" #username: "user" #password: "secret" jmx.mappings: #- mbean: 'java.lang:type=Runtime' # attributes: # - attr: Uptime # field: uptime #- mbean: 'java.lang:type=Memory' # attributes: # - attr: HeapMemoryUsage # field: memory.heap_usage # - attr: NonHeapMemoryUsage # field: memory.non_heap_usage # GC Metrics - this depends on what is available on your JVM #- mbean: 'java.lang:type=GarbageCollector,name=ConcurrentMarkSweep' # attributes: # - attr: CollectionTime # field: gc.cms_collection_time # - attr: CollectionCount # field: gc.cms_collection_count jmx.application: jmx.instance: #-------------------------------- Kafka Module ------------------------------- - module: kafka metricsets: ["consumergroup", "partition"] period: 10s hosts: ["localhost:9092"] enabled: true #client_id: metricbeat #retries: 3 #backoff: 250ms # List of Topics to query metadata for. If empty, all topics will be queried. #topics: [] # Optional SSL. By default is off. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # SASL authentication #username: "" #password: "" #------------------------------- Kibana Module ------------------------------- - module: kibana metricsets: ["status"] period: 10s hosts: ["localhost:5601"] basepath: "" enabled: true #----------------------------- Kubernetes Module ----------------------------- # Node metrics, from kubelet: - module: kubernetes metricsets: - container - node - pod - system - volume period: 10s hosts: ["localhost:10255"] enabled: true #bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token #ssl.certificate_authorities: # - /var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt #ssl.certificate: "/etc/pki/client/cert.pem" #ssl.key: "/etc/pki/client/cert.key" # Enriching parameters: add_metadata: true in_cluster: true # When used outside the cluster: #host: node_name #kube_config: ~/.kube/config # State metrics from kube-state-metrics service: - module: kubernetes enabled: true metricsets: - state_node - state_deployment - state_replicaset - state_statefulset - state_pod - state_container period: 10s hosts: ["kube-state-metrics:8080"] # Enriching parameters: add_metadata: true in_cluster: true # When used outside the cluster: #host: node_name #kube_config: ~/.kube/config # Kubernetes events - module: kubernetes enabled: true metricsets: - event # Kubernetes API server - module: kubernetes enabled: true metricsets: - apiserver hosts: ["https://${KUBERNETES_SERVICE_HOST}:${KUBERNETES_SERVICE_PORT}"] #--------------------------------- kvm Module -------------------------------- - module: kvm metricsets: ["dommemstat"] enabled: true period: 10s hosts: ["unix:///var/run/libvirt/libvirt-sock"] # For remote hosts, setup network access in libvirtd.conf # and use the tcp scheme: # hosts: [ "tcp://<host>:16509" ] # Timeout to connect to Libvirt server #timeout: 1s #------------------------------ Logstash Module ------------------------------ - module: logstash metricsets: ["node", "node_stats"] enabled: true period: 10s hosts: ["localhost:9600"] #------------------------------ Memcached Module ----------------------------- - module: memcached metricsets: ["stats"] period: 10s hosts: ["localhost:11211"] enabled: true #------------------------------- MongoDB Module ------------------------------ - module: mongodb metricsets: ["dbstats", "status", "collstats", "metrics", "replstatus"] period: 10s enabled: true # The hosts must be passed as MongoDB URLs in the format: # [mongodb://][user:pass@]host[:port]. # The username and password can also be set using the respective configuration # options. The credentials in the URL take precedence over the username and # password configuration options. hosts: ["localhost:27017"] # Optional SSL. By default is off. #ssl.enabled: true # Mode of verification of server certificate ('none' or 'full') #ssl.verification_mode: 'full' # List of root certificates for TLS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Username to use when connecting to MongoDB. Empty by default. #username: user # Password to use when connecting to MongoDB. Empty by default. #password: pass #-------------------------------- Munin Module ------------------------------- - module: munin metricsets: ["node"] enabled: true period: 10s hosts: ["localhost:4949"] node.namespace: node #-------------------------------- MySQL Module ------------------------------- - module: mysql metricsets: - "status" # - "galera_status" period: 10s # Host DSN should be defined as "user:pass@tcp(<IP_ADDRESS>:3306)/" # The username and password can either be set in the DSN or using the username # and password config options. Those specified in the DSN take precedence. hosts: ["root:secret@tcp(<IP_ADDRESS>:3306)/"] # Username of hosts. Empty by default. #username: root # Password of hosts. Empty by default. #password: secret # By setting raw to true, all raw fields from the status metricset will be added to the event. #raw: false #-------------------------------- Nginx Module ------------------------------- - module: nginx metricsets: ["stubstatus"] enabled: true period: 10s # Nginx hosts hosts: ["http://<IP_ADDRESS>"] # Path to server status. Default server-status server_status_path: "server-status" #------------------------------- PHP_FPM Module ------------------------------ - module: php_fpm metricsets: - pool #- process enabled: true period: 10s status_path: "/status" hosts: ["localhost:8080"] #----------------------------- PostgreSQL Module ----------------------------- - module: postgresql enabled: true metricsets: # Stats about every PostgreSQL database - database # Stats about the background writer process's activity - bgwriter # Stats about every PostgreSQL process - activity period: 10s # The host must be passed as PostgreSQL URL. Example: # postgres://localhost:5432?sslmode=disable # The available parameters are documented here: # https://godoc.org/github.com/lib/pq#hdr-Connection_String_Parameters hosts: ["postgres://localhost:5432"] # Username to use when connecting to PostgreSQL. Empty by default. #username: user # Password to use when connecting to PostgreSQL. Empty by default. #password: pass #----------------------------- Prometheus Module ----------------------------- - module: prometheus metricsets: ["stats"] enabled: true period: 10s hosts: ["localhost:9090"] #metrics_path: /metrics #namespace: example - module: prometheus metricsets: ["collector"] enabled: true period: 10s hosts: ["localhost:9090"] #metrics_path: /metrics #namespace: example # This can be used for service account based authorization: # bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token #ssl.certificate_authorities: # - /var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt #------------------------------ RabbitMQ Module ------------------------------ - module: rabbitmq metricsets: ["node", "queue", "connection"] enabled: true period: 10s hosts: ["localhost:15672"] # Management path prefix, if `management.path_prefix` is set in RabbitMQ # configuration, it has to be set to the same value. #management_path_prefix: "" #username: guest #password: guest #-------------------------------- Redis Module ------------------------------- - module: redis metricsets: ["info", "keyspace"] enabled: true period: 10s # Redis hosts hosts: ["<IP_ADDRESS>:6379"] # Timeout after which time a metricset should return an error # Timeout is by default defined as period, as a fetch of a metricset # should never take longer then period, as otherwise calls can pile up. #timeout: 1s # Optional fields to be added to each event #fields: # datacenter: west # Network type to be used for redis connection. Default: tcp #network: tcp # Max number of concurrent connections. Default: 10 #maxconn: 10 # Filters can be used to reduce the number of fields sent. #processors: # - include_fields: # fields: ["beat", "metricset", "redis.info.stats"] # Redis AUTH password. Empty by default. #password: foobared #------------------------------- traefik Module ------------------------------ - module: traefik metricsets: ["health"] period: 10s hosts: ["localhost:8080"] #-------------------------------- uwsgi Module ------------------------------- - module: uwsgi metricsets: ["status"] enable: true period: 10s hosts: ["tcp://<IP_ADDRESS>:9191"] #------------------------------- vSphere Module ------------------------------ - module: vsphere enabled: true metricsets: ["datastore", "host", "virtualmachine"] period: 10s hosts: ["https://localhost/sdk"] username: "user" password: "password" # If insecure is true, don't verify the server's certificate chain insecure: false # Get custom fields when using virtualmachine metric set. Default false. # get_custom_fields: false #------------------------------- Windows Module ------------------------------ - module: windows metricsets: ["perfmon"] enabled: true period: 10s perfmon.ignore_non_existent_counters: true perfmon.counters: # - instance_label: processor.name # instance_name: total # measurement_label: processor.time.total.pct # query: '\Processor Information(_Total)\% Processor Time' - module: windows metricsets: ["service"] enabled: true period: 60s #------------------------------ ZooKeeper Module ----------------------------- - module: zookeeper enabled: true metricsets: ["mntr"] period: 10s hosts: ["localhost:2181"] #================================ General ====================================== # The name of the shipper that publishes the network data. It can be used to group # all the transactions sent by a single shipper in the web interface. # If this options is not defined, the hostname is used. #name: # The tags of the shipper are included in their own field with each # transaction published. Tags make it easy to group servers by different # logical properties. #tags: ["service-X", "web-tier"] # Optional fields that you can specify to add additional information to the # output. Fields can be scalar values, arrays, dictionaries, or any nested # combination of these. #fields: # env: staging # If this option is set to true, the custom fields are stored as top-level # fields in the output document instead of being grouped under a fields # sub-dictionary. Default is false. #fields_under_root: false # Internal queue configuration for buffering events to be published. #queue: # Queue type by name (default 'mem') # The memory queue will present all available events (up to the outputs # bulk_max_size) to the output, the moment the output is ready to server # another batch of events. #mem: # Max number of events the queue can buffer. #events: 4096 # Hints the minimum number of events stored in the queue, # before providing a batch of events to the outputs. # The default value is set to 2048. # A value of 0 ensures events are immediately available # to be sent to the outputs. #flush.min_events: 2048 # Maximum duration after which events are available to the outputs, # if the number of events stored in the queue is < min_flush_events. #flush.timeout: 1s # The spool queue will store events in a local spool file, before # forwarding the events to the outputs. # # Beta: spooling to disk is currently a beta feature. Use with care. # # The spool file is a circular buffer, which blocks once the file/buffer is full. # Events are put into a write buffer and flushed once the write buffer # is full or the flush_timeout is triggered. # Once ACKed by the output, events are removed immediately from the queue, # making space for new events to be persisted. #spool: # The file namespace configures the file path and the file creation settings. # Once the file exists, the `size`, `page_size` and `prealloc` settings # will have no more effect. #file: # Location of spool file. The default value is ${path.data}/spool.dat. #path: "${path.data}/spool.dat" # Configure file permissions if file is created. The default value is 0600. #permissions: 0600 # File size hint. The spool blocks, once this limit is reached. The default value is 100 MiB. #size: 100MiB # The files page size. A file is split into multiple pages of the same size. The default value is 4KiB. #page_size: 4KiB # If prealloc is set, the required space for the file is reserved using # truncate. The default value is true. #prealloc: true # Spool writer settings # Events are serialized into a write buffer. The write buffer is flushed if: # - The buffer limit has been reached. # - The configured limit of buffered events is reached. # - The flush timeout is triggered. #write: # Sets the write buffer size. #buffer_size: 1MiB # Maximum duration after which events are flushed, if the write buffer # is not full yet. The default value is 1s. #flush.timeout: 1s # Number of maximum buffered events. The write buffer is flushed once the # limit is reached. #flush.events: 16384 # Configure the on-disk event encoding. The encoding can be changed # between restarts. # Valid encodings are: json, ubjson, and cbor. #codec: cbor #read: # Reader flush timeout, waiting for more events to become available, so # to fill a complete batch, as required by the outputs. # If flush_timeout is 0, all available events are forwarded to the # outputs immediately. # The default value is 0s. #flush.timeout: 0s # Sets the maximum number of CPUs that can be executing simultaneously. The # default is the number of logical CPUs available in the system. #max_procs: #================================ Processors =================================== # Processors are used to reduce the number of fields in the exported event or to # enhance the event with external metadata. This section defines a list of # processors that are applied one by one and the first one receives the initial # event: # # event -> filter1 -> event1 -> filter2 ->event2 ... # # The supported processors are drop_fields, drop_event, include_fields, # decode_json_fields, and add_cloud_metadata. # # For example, you can use the following processors to keep the fields that # contain CPU load percentages, but remove the fields that contain CPU ticks # values: # #processors: #- include_fields: # fields: ["cpu"] #- drop_fields: # fields: ["cpu.user", "cpu.system"] # # The following example drops the events that have the HTTP response code 200: # #processors: #- drop_event: # when: # equals: # http.code: 200 # # The following example renames the field a to b: # #processors: #- rename: # fields: # - from: "a" # to: "b" # # The following example tokenizes the string into fields: # #processors: #- dissect: # tokenizer: "%{key1} - %{key2}" # field: "message" # target_prefix: "dissect" # # The following example enriches each event with metadata from the cloud # provider about the host machine. It works on EC2, GCE, DigitalOcean, # Tencent Cloud, and Alibaba Cloud. # #processors: #- add_cloud_metadata: ~ # # The following example enriches each event with the machine's local time zone # offset from UTC. # #processors: #- add_locale: # format: offset # # The following example enriches each event with docker metadata, it matches # given fields to an existing container id and adds info from that container: # #processors: #- add_docker_metadata: # host: "unix:///var/run/docker.sock" # match_fields: ["system.process.cgroup.id"] # match_pids: ["process.pid", "process.ppid"] # match_source: true # match_source_index: 4 # match_short_id: false # cleanup_timeout: 60 # # To connect to Docker over TLS you must specify a client and CA certificate. # #ssl: # # certificate_authority: "/etc/pki/root/ca.pem" # # certificate: "/etc/pki/client/cert.pem" # # key: "/etc/pki/client/cert.key" # # The following example enriches each event with docker metadata, it matches # container id from log path available in `source` field (by default it expects # it to be /var/lib/docker/containers/*/*.log). # #processors: #- add_docker_metadata: ~ # # The following example enriches each event with host metadata. # #processors: #- add_host_metadata: # netinfo.enabled: false # # The following example enriches each event with process metadata using # process IDs included in the event. # #processors: #- add_process_metadata: # match_pids: ["system.process.ppid"] # target: system.process.parent # # The following example decodes fields containing JSON strings # and replaces the strings with valid JSON objects. # #processors: #- decode_json_fields: # fields: ["field1", "field2", ...] # process_array: false # max_depth: 1 # target: "" # overwrite_keys: false #============================= Elastic Cloud ================================== # These settings simplify using metricbeat with the Elastic Cloud (https://cloud.elastic.co/). # The cloud.id setting overwrites the `output.elasticsearch.hosts` and # `setup.kibana.host` options. # You can find the `cloud.id` in the Elastic Cloud web UI. #cloud.id: # The cloud.auth setting overwrites the `output.elasticsearch.username` and # `output.elasticsearch.password` settings. The format is `<user>:<pass>`. #cloud.auth: #================================ Outputs ====================================== # Configure what output to use when sending the data collected by the beat. #-------------------------- Elasticsearch output ------------------------------- output.elasticsearch: # Boolean flag to enable or disable the output module. #enabled: true # Array of hosts to connect to. # Scheme and port can be left out and will be set to the default (http and 9200) # In case you specify and additional path, the scheme is required: http://localhost:9200/path # IPv6 addresses should always be defined as: https://[2001:db8::1]:9200 hosts: ["localhost:9200"] # Set gzip compression level. #compression_level: 0 # Configure escaping html symbols in strings. #escape_html: true # Optional protocol and basic auth credentials. #protocol: "https" #username: "elastic" #password: "changeme" # Dictionary of HTTP parameters to pass within the url with index operations. #parameters: #param1: value1 #param2: value2 # Number of workers per Elasticsearch host. #worker: 1 # Optional index name. The default is "metricbeat" plus date # and generates [metricbeat-]YYYY.MM.DD keys. # In case you modify this pattern you must update setup.template.name and setup.template.pattern accordingly. #index: "metricbeat-%{[beat.version]}-%{+yyyy.MM.dd}" # Optional ingest node pipeline. By default no pipeline will be used. #pipeline: "" # Optional HTTP Path #path: "/elasticsearch" # Custom HTTP headers to add to each request #headers: # X-My-Header: Contents of the header # Proxy server url #proxy_url: http://proxy:3128 # The number of times a particular Elasticsearch index operation is attempted. If # the indexing operation doesn't succeed after this many retries, the events are # dropped. The default is 3. #max_retries: 3 # The maximum number of events to bulk in a single Elasticsearch bulk API index request. # The default is 50. #bulk_max_size: 50 # The number of seconds to wait before trying to reconnect to Elasticsearch # after a network error. After waiting backoff.init seconds, the Beat # tries to reconnect. If the attempt fails, the backoff timer is increased # exponentially up to backoff.max. After a successful connection, the backoff # timer is reset. The default is 1s. #backoff.init: 1s # The maximum number of seconds to wait before attempting to connect to # Elasticsearch after a network error. The default is 60s. #backoff.max: 60s # Configure http request timeout before failing a request to Elasticsearch. #timeout: 90 # Use SSL settings for HTTPS. #ssl.enabled: true # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # SSL configuration. By default is off. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] # Configure what types of renegotiation are supported. Valid options are # never, once, and freely. Default is never. #ssl.renegotiation: never #----------------------------- Logstash output --------------------------------- #output.logstash: # Boolean flag to enable or disable the output module. #enabled: true # The Logstash hosts #hosts: ["localhost:5044"] # Number of workers per Logstash host. #worker: 1 # Set gzip compression level. #compression_level: 3 # Configure escaping html symbols in strings. #escape_html: true # Optional maximum time to live for a connection to Logstash, after which the # connection will be re-established. A value of `0s` (the default) will # disable this feature. # # Not yet supported for async connections (i.e. with the "pipelining" option set) #ttl: 30s # Optional load balance the events between the Logstash hosts. Default is false. #loadbalance: false # Number of batches to be sent asynchronously to Logstash while processing # new batches. #pipelining: 2 # If enabled only a subset of events in a batch of events is transferred per # transaction. The number of events to be sent increases up to `bulk_max_size` # if no error is encountered. #slow_start: false # The number of seconds to wait before trying to reconnect to Logstash # after a network error. After waiting backoff.init seconds, the Beat # tries to reconnect. If the attempt fails, the backoff timer is increased # exponentially up to backoff.max. After a successful connection, the backoff # timer is reset. The default is 1s. #backoff.init: 1s # The maximum number of seconds to wait before attempting to connect to # Logstash after a network error. The default is 60s. #backoff.max: 60s # Optional index name. The default index name is set to metricbeat # in all lowercase. #index: 'metricbeat' # SOCKS5 proxy server URL #proxy_url: socks5://user:password@socks5-server:2233 # Resolve names locally when using a proxy server. Defaults to false. #proxy_use_local_resolver: false # Enable SSL support. SSL is automatically enabled, if any SSL setting is set. #ssl.enabled: true # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # Optional SSL configuration options. SSL is off by default. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] # Configure what types of renegotiation are supported. Valid options are # never, once, and freely. Default is never. #ssl.renegotiation: never # The number of times to retry publishing an event after a publishing failure. # After the specified number of retries, the events are typically dropped. # Some Beats, such as Filebeat and Winlogbeat, ignore the max_retries setting # and retry until all events are published. Set max_retries to a value less # than 0 to retry until all events are published. The default is 3. #max_retries: 3 # The maximum number of events to bulk in a single Logstash request. The # default is 2048. #bulk_max_size: 2048 # The number of seconds to wait for responses from the Logstash server before # timing out. The default is 30s. #timeout: 30s #------------------------------- Kafka output ---------------------------------- #output.kafka: # Boolean flag to enable or disable the output module. #enabled: true # The list of Kafka broker addresses from where to fetch the cluster metadata. # The cluster metadata contain the actual Kafka brokers events are published # to. #hosts: ["localhost:9092"] # The Kafka topic used for produced events. The setting can be a format string # using any event field. To set the topic from document type use `%{[type]}`. #topic: beats # The Kafka event key setting. Use format string to create unique event key. # By default no event key will be generated. #key: '' # The Kafka event partitioning strategy. Default hashing strategy is `hash` # using the `output.kafka.key` setting or randomly distributes events if # `output.kafka.key` is not configured. #partition.hash: # If enabled, events will only be published to partitions with reachable # leaders. Default is false. #reachable_only: false # Configure alternative event field names used to compute the hash value. # If empty `output.kafka.key` setting will be used. # Default value is empty list. #hash: [] # Authentication details. Password is required if username is set. #username: '' #password: '' # Kafka version metricbeat is assumed to run against. Defaults to the "1.0.0". #version: '1.0.0' # Configure JSON encoding #codec.json: # Pretty print json event #pretty: false # Configure escaping html symbols in strings. #escape_html: true # Metadata update configuration. Metadata do contain leader information # deciding which broker to use when publishing. #metadata: # Max metadata request retry attempts when cluster is in middle of leader # election. Defaults to 3 retries. #retry.max: 3 # Waiting time between retries during leader elections. Default is 250ms. #retry.backoff: 250ms # Refresh metadata interval. Defaults to every 10 minutes. #refresh_frequency: 10m # The number of concurrent load-balanced Kafka output workers. #worker: 1 # The number of times to retry publishing an event after a publishing failure. # After the specified number of retries, the events are typically dropped. # Some Beats, such as Filebeat, ignore the max_retries setting and retry until # all events are published. Set max_retries to a value less than 0 to retry # until all events are published. The default is 3. #max_retries: 3 # The maximum number of events to bulk in a single Kafka request. The default # is 2048. #bulk_max_size: 2048 # The number of seconds to wait for responses from the Kafka brokers before # timing out. The default is 30s. #timeout: 30s # The maximum duration a broker will wait for number of required ACKs. The # default is 10s. #broker_timeout: 10s # The number of messages buffered for each Kafka broker. The default is 256. #channel_buffer_size: 256 # The keep-alive period for an active network connection. If 0s, keep-alives # are disabled. The default is 0 seconds. #keep_alive: 0 # Sets the output compression codec. Must be one of none, snappy and gzip. The # default is gzip. #compression: gzip # Set the compression level. Currently only gzip provides a compression level # between 0 and 9. The default value is chosen by the compression algorithm. #compression_level: 4 # The maximum permitted size of JSON-encoded messages. Bigger messages will be # dropped. The default value is 1000000 (bytes). This value should be equal to # or less than the broker's message.max.bytes. #max_message_bytes: 1000000 # The ACK reliability level required from broker. 0=no response, 1=wait for # local commit, -1=wait for all replicas to commit. The default is 1. Note: # If set to 0, no ACKs are returned by Kafka. Messages might be lost silently # on error. #required_acks: 1 # The configurable ClientID used for logging, debugging, and auditing # purposes. The default is "beats". #client_id: beats # Enable SSL support. SSL is automatically enabled, if any SSL setting is set. #ssl.enabled: true # Optional SSL configuration options. SSL is off by default. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] # Configure what types of renegotiation are supported. Valid options are # never, once, and freely. Default is never. #ssl.renegotiation: never #------------------------------- Redis output ---------------------------------- #output.redis: # Boolean flag to enable or disable the output module. #enabled: true # Configure JSON encoding #codec.json: # Pretty print json event #pretty: false # Configure escaping html symbols in strings. #escape_html: true # The list of Redis servers to connect to. If load balancing is enabled, the # events are distributed to the servers in the list. If one server becomes # unreachable, the events are distributed to the reachable servers only. #hosts: ["localhost:6379"] # The Redis port to use if hosts does not contain a port number. The default # is 6379. #port: 6379 # The name of the Redis list or channel the events are published to. The # default is metricbeat. #key: metricbeat # The password to authenticate with. The default is no authentication. #password: # The Redis database number where the events are published. The default is 0. #db: 0 # The Redis data type to use for publishing events. If the data type is list, # the Redis RPUSH command is used. If the data type is channel, the Redis # PUBLISH command is used. The default value is list. #datatype: list # The number of workers to use for each host configured to publish events to # Redis. Use this setting along with the loadbalance option. For example, if # you have 2 hosts and 3 workers, in total 6 workers are started (3 for each # host). #worker: 1 # If set to true and multiple hosts or workers are configured, the output # plugin load balances published events onto all Redis hosts. If set to false, # the output plugin sends all events to only one host (determined at random) # and will switch to another host if the currently selected one becomes # unreachable. The default value is true. #loadbalance: true # The Redis connection timeout in seconds. The default is 5 seconds. #timeout: 5s # The number of times to retry publishing an event after a publishing failure. # After the specified number of retries, the events are typically dropped. # Some Beats, such as Filebeat, ignore the max_retries setting and retry until # all events are published. Set max_retries to a value less than 0 to retry # until all events are published. The default is 3. #max_retries: 3 # The number of seconds to wait before trying to reconnect to Redis # after a network error. After waiting backoff.init seconds, the Beat # tries to reconnect. If the attempt fails, the backoff timer is increased # exponentially up to backoff.max. After a successful connection, the backoff # timer is reset. The default is 1s. #backoff.init: 1s # The maximum number of seconds to wait before attempting to connect to # Redis after a network error. The default is 60s. #backoff.max: 60s # The maximum number of events to bulk in a single Redis request or pipeline. # The default is 2048. #bulk_max_size: 2048 # The URL of the SOCKS5 proxy to use when connecting to the Redis servers. The # value must be a URL with a scheme of socks5://. #proxy_url: # This option determines whether Redis hostnames are resolved locally when # using a proxy. The default value is false, which means that name resolution # occurs on the proxy server. #proxy_use_local_resolver: false # Enable SSL support. SSL is automatically enabled, if any SSL setting is set. #ssl.enabled: true # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # Optional SSL configuration options. SSL is off by default. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] # Configure what types of renegotiation are supported. Valid options are # never, once, and freely. Default is never. #ssl.renegotiation: never #------------------------------- File output ----------------------------------- #output.file: # Boolean flag to enable or disable the output module. #enabled: true # Configure JSON encoding #codec.json: # Pretty print json event #pretty: false # Configure escaping html symbols in strings. #escape_html: true # Path to the directory where to save the generated files. The option is # mandatory. #path: "/tmp/metricbeat" # Name of the generated files. The default is `metricbeat` and it generates # files: `metricbeat`, `metricbeat.1`, `metricbeat.2`, etc. #filename: metricbeat # Maximum size in kilobytes of each file. When this size is reached, and on # every metricbeat restart, the files are rotated. The default value is 10240 # kB. #rotate_every_kb: 10000 # Maximum number of files under path. When this number of files is reached, # the oldest file is deleted and the rest are shifted from last to first. The # default is 7 files. #number_of_files: 7 # Permissions to use for file creation. The default is 0600. #permissions: 0600 #----------------------------- Console output --------------------------------- #output.console: # Boolean flag to enable or disable the output module. #enabled: true # Configure JSON encoding #codec.json: # Pretty print json event #pretty: false # Configure escaping html symbols in strings. #escape_html: true #================================= Paths ====================================== # The home path for the metricbeat installation. This is the default base path # for all other path settings and for miscellaneous files that come with the # distribution (for example, the sample dashboards). # If not set by a CLI flag or in the configuration file, the default for the # home path is the location of the binary. #path.home: # The configuration path for the metricbeat installation. This is the default # base path for configuration files, including the main YAML configuration file # and the Elasticsearch template file. If not set by a CLI flag or in the # configuration file, the default for the configuration path is the home path. #path.config: ${path.home} # The data path for the metricbeat installation. This is the default base path # for all the files in which metricbeat needs to store its data. If not set by a # CLI flag or in the configuration file, the default for the data path is a data # subdirectory inside the home path. #path.data: ${path.home}/data # The logs path for a metricbeat installation. This is the default location for # the Beat's log files. If not set by a CLI flag or in the configuration file, # the default for the logs path is a logs subdirectory inside the home path. #path.logs: ${path.home}/logs #================================ Keystore ========================================== # Location of the Keystore containing the keys and their sensitive values. #keystore.path: "${path.config}/beats.keystore" #============================== Dashboards ===================================== # These settings control loading the sample dashboards to the Kibana index. Loading # the dashboards are disabled by default and can be enabled either by setting the # options here, or by using the `-setup` CLI flag or the `setup` command. #setup.dashboards.enabled: false # The directory from where to read the dashboards. The default is the `kibana` # folder in the home path. #setup.dashboards.directory: ${path.home}/kibana # The URL from where to download the dashboards archive. It is used instead of # the directory if it has a value. #setup.dashboards.url: # The file archive (zip file) from where to read the dashboards. It is used instead # of the directory when it has a value. #setup.dashboards.file: # In case the archive contains the dashboards from multiple Beats, this lets you # select which one to load. You can load all the dashboards in the archive by # setting this to the empty string. #setup.dashboards.beat: metricbeat # The name of the Kibana index to use for setting the configuration. Default is ".kibana" #setup.dashboards.kibana_index: .kibana # The Elasticsearch index name. This overwrites the index name defined in the # dashboards and index pattern. Example: testbeat-* #setup.dashboards.index: # Always use the Kibana API for loading the dashboards instead of autodetecting # how to install the dashboards by first querying Elasticsearch. #setup.dashboards.always_kibana: false # If true and Kibana is not reachable at the time when dashboards are loaded, # it will retry to reconnect to Kibana instead of exiting with an error. #setup.dashboards.retry.enabled: false # Duration interval between Kibana connection retries. #setup.dashboards.retry.interval: 1s # Maximum number of retries before exiting with an error, 0 for unlimited retrying. #setup.dashboards.retry.maximum: 0 #============================== Template ===================================== # A template is used to set the mapping in Elasticsearch # By default template loading is enabled and the template is loaded. # These settings can be adjusted to load your own template or overwrite existing ones. # Set to false to disable template loading. #setup.template.enabled: true # Template name. By default the template name is "metricbeat-%{[beat.version]}" # The template name and pattern has to be set in case the elasticsearch index pattern is modified. #setup.template.name: "metricbeat-%{[beat.version]}" # Template pattern. By default the template pattern is "-%{[beat.version]}-*" to apply to the default index settings. # The first part is the version of the beat and then -* is used to match all daily indices. # The template name and pattern has to be set in case the elasticsearch index pattern is modified. #setup.template.pattern: "metricbeat-%{[beat.version]}-*" # Path to fields.yml file to generate the template #setup.template.fields: "${path.config}/fields.yml" # A list of fields to be added to the template and Kibana index pattern. Also # specify setup.template.overwrite: true to overwrite the existing template. # This setting is experimental. #setup.template.append_fields: #- name: field_name # type: field_type # Enable json template loading. If this is enabled, the fields.yml is ignored. #setup.template.json.enabled: false # Path to the json template file #setup.template.json.path: "${path.config}/template.json" # Name under which the template is stored in Elasticsearch #setup.template.json.name: "" # Overwrite existing template #setup.template.overwrite: false # Elasticsearch template settings setup.template.settings: # A dictionary of settings to place into the settings.index dictionary # of the Elasticsearch template. For more details, please check # https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html #index: #number_of_shards: 1 #codec: best_compression #number_of_routing_shards: 30 # A dictionary of settings for the _source field. For more details, please check # https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-source-field.html #_source: #enabled: false #============================== Kibana ===================================== # Starting with Beats version 6.0.0, the dashboards are loaded via the Kibana API. # This requires a Kibana endpoint configuration. setup.kibana: # Kibana Host # Scheme and port can be left out and will be set to the default (http and 5601) # In case you specify and additional path, the scheme is required: http://localhost:5601/path # IPv6 addresses should always be defined as: https://[2001:db8::1]:5601 #host: "localhost:5601" # Optional protocol and basic auth credentials. #protocol: "https" #username: "elastic" #password: "changeme" # Optional HTTP Path #path: "" # Use SSL settings for HTTPS. Default is true. #ssl.enabled: true # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # SSL configuration. By default is off. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] #================================ Logging ====================================== # There are four options for the log output: file, stderr, syslog, eventlog # The file output is the default. # Sets log level. The default log level is info. # Available log levels are: error, warning, info, debug #logging.level: info # Enable debug output for selected components. To enable all selectors use ["*"] # Other available selectors are "beat", "publish", "service" # Multiple selectors can be chained. #logging.selectors: [ ] # Send all logging output to syslog. The default is false. #logging.to_syslog: false # Send all logging output to Windows Event Logs. The default is false. #logging.to_eventlog: false # If enabled, metricbeat periodically logs its internal metrics that have changed # in the last period. For each metric that changed, the delta from the value at # the beginning of the period is logged. Also, the total values for # all non-zero internal metrics are logged on shutdown. The default is true. #logging.metrics.enabled: true # The period after which to log the internal metrics. The default is 30s. #logging.metrics.period: 30s # Logging to rotating files. Set logging.to_files to false to disable logging to # files. logging.to_files: true logging.files: # Configure the path where the logs are written. The default is the logs directory # under the home path (the binary location). #path: /var/log/metricbeat # The name of the files where the logs are written to. #name: metricbeat # Configure log file size limit. If limit is reached, log file will be # automatically rotated #rotateeverybytes: 10485760 # = 10MB # Number of rotated log files to keep. Oldest files will be deleted first. #keepfiles: 7 # The permissions mask to apply when rotating log files. The default value is 0600. # Must be a valid Unix-style file permissions mask expressed in octal notation. #permissions: 0600 # Enable log file rotation on time intervals in addition to size-based rotation. # Intervals must be at least 1s. Values of 1m, 1h, 24h, 7*24h, 30*24h, and 365*24h # are boundary-aligned with minutes, hours, days, weeks, months, and years as # reported by the local system clock. All other intervals are calculated from the # unix epoch. Defaults to disabled. #interval: 0 # Set to true to log messages in json format. #logging.json: false #============================== Xpack Monitoring ===================================== # metricbeat can export internal metrics to a central Elasticsearch monitoring cluster. # This requires xpack monitoring to be enabled in Elasticsearch. # The reporting is disabled by default. # Set to true to enable the monitoring reporter. #xpack.monitoring.enabled: false # Uncomment to send the metrics to Elasticsearch. Most settings from the # Elasticsearch output are accepted here as well. Any setting that is not set is # automatically inherited from the Elasticsearch output configuration, so if you # have the Elasticsearch output configured, you can simply uncomment the # following line, and leave the rest commented out. #xpack.monitoring.elasticsearch: # Array of hosts to connect to. # Scheme and port can be left out and will be set to the default (http and 9200) # In case you specify and additional path, the scheme is required: http://localhost:9200/path # IPv6 addresses should always be defined as: https://[2001:db8::1]:9200 #hosts: ["localhost:9200"] # Set gzip compression level. #compression_level: 0 # Optional protocol and basic auth credentials. #protocol: "https" #username: "beats_system" #password: "changeme" # Dictionary of HTTP parameters to pass within the url with index operations. #parameters: #param1: value1 #param2: value2 # Custom HTTP headers to add to each request #headers: # X-My-Header: Contents of the header # Proxy server url #proxy_url: http://proxy:3128 # The number of times a particular Elasticsearch index operation is attempted. If # the indexing operation doesn't succeed after this many retries, the events are # dropped. The default is 3. #max_retries: 3 # The maximum number of events to bulk in a single Elasticsearch bulk API index request. # The default is 50. #bulk_max_size: 50 # The number of seconds to wait before trying to reconnect to Elasticsearch # after a network error. After waiting backoff.init seconds, the Beat # tries to reconnect. If the attempt fails, the backoff timer is increased # exponentially up to backoff.max. After a successful connection, the backoff # timer is reset. The default is 1s. #backoff.init: 1s # The maximum number of seconds to wait before attempting to connect to # Elasticsearch after a network error. The default is 60s. #backoff.max: 60s # Configure http request timeout before failing an request to Elasticsearch. #timeout: 90 # Use SSL settings for HTTPS. #ssl.enabled: true # Configure SSL verification mode. If `none` is configured, all server hosts # and certificates will be accepted. In this mode, SSL based connections are # susceptible to man-in-the-middle attacks. Use only for testing. Default is # `full`. #ssl.verification_mode: full # List of supported/valid TLS versions. By default all TLS versions 1.0 up to # 1.2 are enabled. #ssl.supported_protocols: [TLSv1.0, TLSv1.1, TLSv1.2] # SSL configuration. By default is off. # List of root certificates for HTTPS server verifications #ssl.certificate_authorities: ["/etc/pki/root/ca.pem"] # Certificate for SSL client authentication #ssl.certificate: "/etc/pki/client/cert.pem" # Client Certificate Key #ssl.key: "/etc/pki/client/cert.key" # Optional passphrase for decrypting the Certificate Key. #ssl.key_passphrase: '' # Configure cipher suites to be used for SSL connections #ssl.cipher_suites: [] # Configure curve types for ECDHE based cipher suites #ssl.curve_types: [] # Configure what types of renegotiation are supported. Valid options are # never, once, and freely. Default is never. #ssl.renegotiation: never #metrics.period: 10s #state.period: 1m #================================ HTTP Endpoint ====================================== # Each beat can expose internal metrics through a HTTP endpoint. For security # reasons the endpoint is disabled by default. This feature is currently experimental. # Stats can be access through http://localhost:5066/stats . For pretty JSON output # append ?pretty to the URL. # Defines if the HTTP endpoint is enabled. #http.enabled: false # The HTTP endpoint will bind to this hostname or IP address. It is recommended to use only localhost. #http.host: localhost # Port on which the HTTP endpoint will bind. Default is 5066. #http.port: 5066 #============================= Process Security ================================ # Enable or disable seccomp system call filtering on Linux. Default is enabled. #seccomp.enabled: true


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2013
December, 2013
The Language of Flowers: A Novel
Vanessa Diffenbaugh
November, 2013
The Hare with Amber Eyes: A Hidden Inheritance
Edmund de Waal
October, 2013
Crazy Rich Asians
Kevin Kwan
September, 2013
The Woman Upstairs
Claire Messud
August, 2013
Live by Night: A Novel (Joe Coughlin Series)
Dennis Lehane
June, 2013
The Art Forger: A Novel
B. A. Shapiro
May, 2013
The Dinner
Herman Koch
April, 2013
Nemesis
Philip Roth
March, 2013
The Dovekeepers: A Novel
Alice Hoffman
February, 2013
Major Pettigrew's Last Stand: A Novel
Helen Simonson
January, 2013
The Book of Mormon Girl: A Memoir of an American Faith
Joanna Brooks


This application (caller) can send a message to background service (callee) using a messagePort.
Background service will reply to every message with its own message and this message will be displayed.
Use buttons on the bottom to send messages to background service.


--- layout: page title: About header-img: "img/about-bg.png" ---
Non-binary coder making their way from Houston to Denver. Loves dogs, video games, and youtube (and coding).


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Here you can find a collection of the audio samples i recorded during the past years. There are many industrial/junk percussions, even self-built instruments, or outdoor structure played with sticks, mallet, etc. Many things are sampled multiple times, with also different samples for low / high dynamics.


My Coding Skills
Personally I believe Coding isn't about what you know; it's about what you can figure out
Below are are the programming languages that I have mastered
HTML5
HTML- stands for Hypertext Markup Language, basically its the language used to make the structure of website pages.
CSS 3
CSS- stands for Cascading Style Sheet, basically its what we use to make the website pages look pretty and appealing to the eye.
JavaScript
JavaScript- is a scripting language. It's used to "Give behaviour " to web pages,in otherwords it's for making websites interactive