Introduction. Scroll up a little bit and click on the “Test” button: This time we’re not configuring a trigger for our lambda function, so it really doesn’t matter what the test event has. Amazon CloudWatch Lambda Insights, now available in preview, enables you to monitor, troubleshoot, and optimize the performance of AWS Lambda functions. There’s also a function called “put_metric_data” in the Boto 3 official docs. Amazon Lambda is a compute service that runs code in response to events and automatically manages the compute resources required by that code. Create a new Python file (.py extension) and start by adding the Boto 3 import: We need to create a CloudWatch client to send metric data using the Boto 3 SDK. All CloudWatch metrics are prorated on an hourly basis. Examples are CPU usage of an EC2 instance or number of requests made towards your API. CloudWatch metrics are aggregated by pod, service, and namespace using their name. Metrics reported by various AWS services (such as EC2, RDS, and Lambda) are stored in their respective namespaces, which are usually named after the AWS service that send s the metrics (more on that below). In my next post, we will take a deep dive into CloudWatch Logs to see how you can use it to help debug issues and the limits with CloudWatch Logs. The lambda function is already created and it has the code we just tested locally. Go back to the AWS Lambda page and click on the “CloudWatch Events” trigger in the left panel. By sending those metrics to AWS CloudWatch, I was able to act proactively with the infrastructure, either by restarting the app or by scaling out the infrastructure. You will have to parameterize some of the fields such as API name and region so that the template can be used for different stages and regions. CloudWatch Insights let you go farther, using analysis of structured log data to automatically generate metrics based on your application logs - all without any extra code. Since most of them follow a certain convention, we should automate the process of creating them. You can also set up dashboards in CloudWatch at a cost of $3 per month per dashboard (first 3 are free). CloudWatch also gives you the capability to build in custom metrics, with simple API calls populating CloudWatch with the metrics that are important to your application. AWS Lambda is monitoring functions for you automatically, while it reports metrics through the Amazon CloudWatch. If you don’t have Python installed, you can install it here. How AWS CloudWatch Handles Metrics Namespaces. In this post, we will take a deep dive into CloudWatch Metrics to see how you can use it to monitor your Lambda functions and its limitations. With AWS Lambda we can use the log stream functionality of CloudWatch to monitor the execution of our functions. Get alerted as soon as an issue occurs and instantly drill down to see a virtual stack trace & correlated logs. Metrics are data about the performance of your systems. Remember, we set this up so the user only has permissions to send custom metrics data to CloudWatch. CloudWatch Lambda Insights is a monitoring and troubleshooting solution for serverless applications running on AWS Lambda. Name the policy (I typed “put-custom-metric”) and then click on the blue “Create policy” button: Great! Set the alert threshold to ~80% of the regional concurrency limit (defaults to 1000 in most regions). and Q: Can I delete any metrics? Name the function (I typed “cool-kpis”) and choose “Python 2.7” for the runtime. For APIs, you can also use API Gateway’s Latency and IntegrationLatency metrics instead. Select it. Copy the following JSON definition for the policy: Click on the “JSON” tab and paste the policy you just copied: Click on the blue “Review policy” button. Everything we did here was manual, so you might need to automate at least deployments by using the AWS CLI, Serverless Framework, SAML, or similar services. You may also need to send the metrics somewhere other than CloudWatch. Then click on the orange “Save” button in the upper-righthand corner for the lambda function. However, setting up custom alarms based on events or errors in a log isn’t as straightforward. Go to the Lambda page and click on the orange “Create function” button: If you don’t have any function there, go to the Lambda home page and click on the orange “Create a function” button. I’ve used AWS Lambda to send custom metrics to CloudWatch to collect data on business metrics like purchases made in the application. The AWS SDK for Python is called Boto 3. Check our free transaction tracing tool, Tip: Find application errors and performance problems instantly with Stackify Retrace. Doing this for metrics like CPU load or storage use is trivial. A metricis a time-ordered set of data points, also known as a time series. ... Terraform module to configure ECS Service autoscaling using CloudWatch metrics. CloudWatch Metrics gives you basic metrics, visualization, and alerting while CloudWatch Logs captures everything that is written to stdout and stderr. You can install it simply by running this command on the terminal: In order to avoid having to put the AWS credentials in the code and risk them persisting in version control, we need to configure the AWS credentials in the local files that the AWS SDK will use to interact with the AWS API. You get all the basic telemetry about the health of a function out of the box: In addition, you also have some metrics that are only relevant to specific event sources: In addition to these built-in metrics, you can also record custom metrics and publish them to CloudWatch Metrics. Well, according to the official docs, there’s a command called “put-metric-data”. It’s as simple as creating a Boto 3 client and typing the name of the service we’d like it to interact with: What I like about creating a client in Boto 3 as opposed to other approaches is that it’s a 1:1 relation with the AWS CLI. So if you want it to be every five minutes, type “cron(0 0/5 * * * *)”. Go to the IAM Users page and click on the blue “Add user” button: Create a username (I typed “custom-metrics”) and make sure you select the “Programmatic access” checkbox. The ACloudGuru team created a handy plugin for the Serverless framework. Well, the code is generating random data, but now you have a placeholder to add more complex things like querying a database or making a request to another service. The SDK will make sure to request new credentials when it’s needed. Go to the IAM role page and click on the blue “Create role” button: Make sure the “AWS Service” is selected and click on the “Lambda” link: Click on the blue “Next: Permissions” button to attach the policies we just created. (If this is your first time doing this, it could take 5–20 minutes.) ______________________________________________________________________________________________________________________________. AWS Lambda reports eight different metrics to CloudWatch which we can use for monitoring: Invocations – Counts the number of times Lambda is invoked by an event or an API call. Let’s configure the schedule. the percentage of requests that did not complete successfully. Or you can always read the AWS official docs to get an even better understanding. CloudWatch offers support for both metrics and logging. In the meantime, you can fall back to using a combination of average and max duration. Join us for a 15 minute, group Retrace session, How to Troubleshoot IIS Worker Process (w3wp) High CPU Usage, How to Monitor IIS Performance: From the Basics to Advanced IIS Performance Monitoring, SQL Performance Tuning: 7 Practical Tips for Developers, Looking for New Relic Alternatives & Competitors? The metrics we speak of consist of total invocations, throttles, duration, error, DLQ errors, etc. My preferred approach is to automatically create alerts CloudFormation macros. You’ll now be able to choose the IAM role we created earlier. Overview. Lambda Dashboards; DynamoDB Dashboards; Lambda Dashboards. Type a descriptive name for the event, something like “every-five-minutes”, and a detailed description. For example, the following dashboard is composed of several API Gateway metrics and highlights the health and performance of an API. For APIs, consider including the following: It’s simple and tells me the general health of the API at a glance. These metrics are collected at higher granularity than standard CloudWatch metrics, enabling you to view metric data at near real-time in Datadog. Click on the blue “Next: Review” button. We explored some of the limitations with CloudWatch Metrics. Keep in mind that, in order to follow the tutorial, you’re going to need to be logged to your Amazon AWS account. What are CloudWatch metrics? Choose the “Create a new rule” option for the Rule field. Later, when we check that data is in AWS, you’ll get a better idea of how helpful this will be. To see how close you are to hitting concurrency limits, view these metrics with the Max statistic. It doesn’t matter which OS you use; we’ll create a simple app using the AWS SDK. Click on the blue “Create role” button. If you just want to copy the values, you’ll need to click on the “Show” link (see above). Here are a few tips for building service dashboards: This page has some simple guidelines for designing dashboards. Click on the “JSON” tab and paste the following JSON definition: Click on the blue “Review policy” button. And do you want to hear the best part? But we also need to create a new IAM policy so that our AWS Lambda function can put logs into CloudWatch logs. Now that we have everything we need to test locally, let’s start coding. Scroll down a little bit and replace the code that’s there with the new one: Click on the orange “Save” button in the upper-righthand corner. CloudWatch Lambda Metrics. See you next time! Adding CloudWatch Metrics to your Lambda Function The actual issue here is your Lambda function just needs permission to publish to the logs. You can then use. As a result, they often end up cluttered, confusing to read and slow to render as there are far too many data points on the screen. In this case, it has permissions to CloudWatch and CloudWatch logs. You can then codify the dashboard as an AWS::CloudWatch::Dashboard resource in a CloudFormation template. We saw what you can do with dashboards in CloudWatch and discussed some tips for designing a service dashboard. You can use Amazon CloudWatch to collect and track metrics, collect and monitor log files, and set alarms. Add the following line below the “cloudwatch” client you just created. CloudWatch offers support for both metrics and logging. Next, configure the AWS region where you want to store the custom metrics. The policy has been created. The skill of creating good alerts lies in finding the right balance of metrics, time periods, and thresholds. I have created a custom dashboard and added same metrics so I have managed to get the same diagrams by adding them manually from the list of metrics… Check the policy, scroll down a little bit, and click on the blue “Next: Review” button: Click on the blue “Create user” button to finish creating the user. How do you do that? It will also be useful when there are errors because you’ll be able to see what’s happening. For individual functions, consider adding the following alerts for each: So that’s a lot of alerts we have to set up! Lambda reports concurrency metrics as an aggregate count of the number of instances processing events across a function, version, alias, or AWS Region. Now we’re going to create a user that we’ll attach this policy to. This code is almost ready to be deployed to AWS Lambda. Let’s create a new policy the same way we just did before. series metrics / lambda / aws / serverless / functions / cloudwatch AWS Lambda is a compute service that enables you to build serverless applications without the need to provision or maintain infrastructure resources (e.g., server capacity, network, security patches). Enter a name and description for this alarm. NOTE: If you decide to interact with a private resource in AWS by using the VPC, you need to add the following permissions to the above policy (or create a new one) so that the AWS Lambda function can connect to the internal resources. Go to the IAM Policiespage and click on the blue “Create policy” button: The user we’re going to create will only need to have permissions to put metric data into CloudWatch. You can do this in a number of ways, including: A number of valuable metrics are sadly missing, including: Another problem with CloudWatch Metrics is that its percentile metrics for Lambda doesn’t work consistently. With this preview, you have access to automated dashboards summarizing the performance and health of your Lambda functions that provide visibility into issues such as memory leaks or performance changes caused by new … Template for Solving Matrix Chain Multiplication (MCM) Problem in DP, 10 Things to Learn as a Self-Taught Software Developer, Using custom relation queries to establish Friends and Friendships in Rails and ActiveRecord, Getting your latest releases from Deezer with Python, Serverless-Flow: A CI/CD Branching Workflow Optimized for Speed and Quality, Write custom metrics to stdout, which are then captured by CloudWatch Logs. So leave everything as default, type a name for the event, scroll down a little bit, and click on the orange “Create” button. In this post, we took a deep dive into how you can use CloudWatch Metrics to monitor your Lambda functions. Add this line right after the imports section: Tab the code below so that it becomes part of the function. By generating metrics based on observed log messages we can increase the value of our CloudWatch logs by providing visualizations of the metric data through dashboard, and providing alerts when metrics … When this code is deployed into AWS Lambda, the message we just printed will go to the CloudWatch logs. That’s why we are having four, fifteen-minute product sessions to outline Retrace’s capabilities. By default, several services provide free metrics to resources like Amazon EC2 instances, Amazon EBS volumes, Amazon … Send Lambda Functions usage metrics to … The first thing we need to do is to create an IAM policy in AWS Identity & Access Management with the fewest privileges. In our case, it will generate random numbers, but in a real-world situation, having a schedule for the .lambda to run will be valuable because you’ll see more data in CloudWatch. If you haven't setup the alarm for the Lambda errors (or you want to create a separate alarm for this use case anyway), go to your CloudWatch Console: Look for your Lambda name in the listing of metrics, and click on the checkbox for the row where the metric name is "Invocations". Christian Melendez November 14, 2019 Developer Tips, Tricks & Resources. Copy or download the credentials. A new box will appear with the “CloudWatch Events” name. We’ll create the Lambda function using Python 2.7, so let’s start by installing the Bot Builder SDK for .NET to test locally before going to AWS. For this to work, you need to include the random import line at the beginning of the script: In a real-world application, you would replace that random number with a number that you got, for example, after querying the database. As a rule of thumb, you should limit dashboards to only the most relevant and significant information about the health of a system. Originally published at https://lumigo.io on July 2, 2019. The only difference is that in Python you use an underscore (_) instead of a hyphen (-). We’ll use the same IAM policy that we assigned the user we created to test locally. Creating a metric with a different dimension. CloudWatch-SNS-Lambda integration that sends alarm notification to discord channel. We’re going to deploy the code manually now, which I’ll admit is a bit archaic. Finally, we discussed what alerts you should set up so that you are duly notified when things go wrong. You can go to CloudWatch Metrics page to check if the metrics are visible. Copy the following JSON definition for the policy: Click on the “JSON” tab and paste the policy you just copied: Click on the blue “Review policy” button. Go to the IAM Policies page and click on the blue “Create policy” button: The user we’re going to create will only need to have permissions to put metric data into CloudWatch. Now that we’ve set up all the dependencies we’ll need, it’s time to add the code to send custom metrics. The error rate, i.e. You should now be able to retrieve an access key ID and a secret access key (credentials) that you can use on your local computer to interact with AWS. You can compose your dashboards with any metrics from CloudWatch (including custom metrics). Metrics utility will flush all metrics when adding the 100th metric while subsequent metrics will be aggregated into a new EMF object, for your convenience. This line will send a custom metric for the number of purchases that have been made in the application: You can find a good explanation for each of those parameters in the Boto 3 official docs, but the name makes most of their functions pretty clear. Monitor & debug your serverless application effortlessly! Today’s post is a detailed guide on how to send custom metrics to AWS CloudWatch monitoring using AWS Lambda. Use CloudWatch we can generate metrics from our logs using pattern matching. When you deploy code to AWS Lambda, one of the prerequisites is that you need to indicate what the code’s handler is. Metrics are stored in namespaces, which are akin to folders. Then select the “Schedule expression” option and type the expression in cron format. CloudWatch Lambda Insights gives clearer and easier operational visibility of your capabilities by mechanically collating and summarizing Lambda efficiency metrics, errors, and logs in prebuilt dashboards, saving you from time-consuming, guide work. Now name the role (I typed “put-custom-metric”) and at the bottom, you’ll see the policies that we just selected. This is where it gets a little funny. If you want to learn more about CloudFormation macros and how to create them, check out this excellent post by Alex Debrie. Then select the “Choose an existing role” option for the role. CloudWatch EMF supports a max of 100 metrics. For more information about the metrics that Lambda records, see Working with AWS Lambda function metrics. Humio’s CloudWatch integration sends your AWS CloudWatch Logs and Metrics to Humio by using AWS Lambda functions to ship the data. You’ll see the following screen: Select the “Author from scratch” option—we’ll upload the code we just created. Go to the ~/.aws/config file (if it doesn’t exist, create it) and replace the content there with the following: The value you put in this file is the AWS region code. Scroll down a little bit and you’ll see the event form. CloudWatch EMF uses the same dimensions across all your metrics. This is the code that we’ll deploy to AWS Lambda. When it comes to monitoring latencies, should be using percentiles instead of the average. To facilitate this, we have got an AWS Lambda coded and ready for you to deploy, you can see the full CloudWatch guide here. AWS CloudWatch Logs. At this point, you have to capture the logs from AWS CloudWatch instead. It should look like this: Scroll down a little bit and click on the “Add” button. You would be able to create dashboards to see how the metrics have changed over time. That is due to the fact that CloudWatch, which is the tool for monitoring AWS services, does not automatically track your Lambda functions metrics. This is a critical issue that we have raised with AWS, and hopefully, it will be addressed in the near future. Click on the orange “Create function” button to finish. Go to the ~/.aws/credentials file (if it doesn’t exist, create it) and replace the content there with the following: YOUR_ACCESS_KEY_ID is the access key from the user you just created, and YOUR_SECRET_ACCESS_KEY is the secret access key from that user. Click "Next". The configuration can specify the lambda metrics together with the stats of the metrics to be added. Once you have handcrafted your dashboard. Conclusion. However, it still requires a lot of configuration, especially if you don’t agree with the plugin’s defaults. To help us troubleshoot failures in a function, Lambda logs all requests handled by our function and also automatically stores logs generated by our code through Amazon CloudWatch Logs. In this blog post, I will describe how one can publish a custom metric to the CloudWatch for better monitoring of your Lambda functions cost. And, luckily, when it comes to AWS Lambda, we’re given some nice default metrics out-of-the-box which we can use as a basis for our alarms. We use a Lambda to capture the logged data from the Lambdas that are sent to CloudWatch. So replace those fields with your own access keys values. Now it’s time to create the AWS Lambda function. Start typing the name of the policy and it will appear in the list below. Even though our example isn’t that complex, you had the chance to connect and interact with several AWS services. Lambda then logs all requests handled by your function and stores logs through AWS CloudWatch Logs.. CloudWatch and the Lambda Navigator. The AWS Lambda function will use this to send metrics data to CloudWatch. Getting started will cost you less than you might spend on a cheeseburger. As of today AWS Lambda exposes the following metrics to Clo… — Pulling data from Cloudwatch Insight Logs — Pulling data from Cloudwatch Metrics — Main Lambda Function and publishing data to AWS SNS 5. And that’s it! Want to write better code? The AWS Lambda ULM App uses the Lambda logs via CloudWatch and visualizes operational and performance trends about all the Lambda functions in your account, providing insight … I’m also including a random number generator so that we can get different data when the lambda runs. Beware that you can’t delete metrics—you just have to wait for them to expire as the FAQ page indicates in the questions: Q: What is the retention period of all metrics? Put the most important metrics at the top to create a hierarchy. Set up your free Lumigo account today & start fixing serverless issues in a fraction of the time! Troubleshooting and optimizing your code is easy with integrated errors, logs and code level performance insights. But before I automate things, I like to do things manually so I have a chance to understand what I’m doing when automating. In this case, we’ll send metric data to CloudWatch. If a library to do more complex things is not natively supported in AWS Lambda, you can pack the libraries with the code and upload it to AWS. But that’s not a good security practice, which is why we need an IAM role. If everything went well, you should see something like this printed in the terminal: Great! In CloudWatch metrics are organized in so called namespaces. Starting from scratch, we’re going to finish up this post by leaving a serverless project running on Amazon Web Services (AWS). Most AWS services send predefined metrics to CloudWatch out of the box but it is also possible to send custom metrics. Name this policy (I typed “cloudwatchlogs-write”) and then click on the blue “Create policy” button. Use horizontal annotations to mark SLA thresholds, etc. The solution collects, aggregates, and summarizes system-level metrics including CPU time, memory, disk, and network. Click on the “Test” button again to test the lambda function: Now we wait—it will take some time to see the metrics in AWS. CloudWatch is a service that is used to monitor the operation and performance of an AWS environment. We looked at the metrics that you get out-of-the-box, and how to publish custom metrics. These are: concurrent executions, duration, errors, throttles and number of invocations. When I click on different time ranges, there is still no data available. All that means is that Lambda needs the code’s starting point. With AWS Lambda, you have basic observability built into the platform with CloudWatch. I only had to type “put-” before my “put-custom-metric” policy appeared. For example: With Lambda, a typical function has four CloudWatch metrics emitted: number of invocations, duration, errors, and throttles. Now let’s have some fun and do something more interesting with this project. You can click Actions, View/edit source to see the code behind for the dashboard. If you have 50 Lambda functions in your account, your monitoring tool needs to do GetMetrics API calls on 50 x 4 = 200 metric/dimension combinations. Click on the blue “Next: Permissions” button: Now it’s time to attach the IAM policy we created earlier to this user. 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What’s interesting about the above code is that I put two dimensions (copied below) for the metric: According to the AWS docs, a dimension is “a name/value pair that uniquely identifies a metric.” So first, we’re identifying the metric data by saying that the value is for the “CoolService” purchase app, then we’re specifying that it’s for version 1.0 of the app. However, when a function experiences more than ~100 invocations per minute, the percentile latencies stop working! Name the policy (I typed “put-custom-metric”) and then click on the blue “Cr… Using our standard AWS integration, we poll the relevant CloudWatch metrics and make them available in both our Infrastructure Navigator and in several new built-in dashboards. You can also use Metric Math to create computed metrics and include them in your dashboards. In the next screen, you’ll be able to see which permissions the lambda function has. So let’s wrap the current code into a handler (or def in Python terms). These alarms can perform one or more actions based on the value of the metric or expression that the alarm is tracking, relative to a user defined threshold over a specified number of time periods. So, AWS Lambda includes a set of metrics that can be … To see the definition of a graph in CloudWatch, choose View in metrics from the menu in the top right of the graph. With AWS Lambda, you have basic observability built into the platform with CloudWatch. How do we do this? AWS Lambda is just a way to expose and host your code; it shouldn’t restrict you from doing interesting things. Great! This page is limited to documentation for ingesting AWS Lambda metrics from Amazon CloudWatch. Database Deep Dive | December 2nd at 10am CST, Traces: Retrace’s Troubleshooting Roadmap | December 9th at 10am CST, Centralized Logging 101 | December 16th at 10am CST. Retrace Overview | January 6th at 10am CST. So, putting everything together, the code should look like this: Run the script. AWS Lambda monitors Lambda functions, and reports metrics through Amazon CloudWatch. lambda-metrics-maven-plugin is a tool (delivered as a Maven plugin) that automates the setup of Cloudwatch Metric Filters by inspecting your compiled Lambda function code and using the AWS Java Cloudwatch SDK to create the appropriate Metric Filters based on the metric fields you annotated. You also need to have PIP installed on your local machine. We know you’re busy, especially during the holiday season. The console also shows reports from CloudWatch Logs Insights that are compiled from information in your function's logs. For Python scripts, AWS Lambda needs the name of the file and the name of the function where the code workflow starts. So let’s keep it simple and copy the code from the Wrap the code into a handler section that we created earlier in this guide.