With digitalization and the cloud assuming responsibility for the development and deployment of new features in software applications, error handling is a critical activity that aids in faster deployment. Any error in the chain, from writing code to deploying to monitoring performance, can degrade customer experience, increase costs, or immediately disrupt critical services. Amazon has launched DevOps Guru, a fully managed operations service that assists developers and operators in improving application performance and availability. DevOps Guru relieves you of the administrative burden of identifying operational issues, allowing you to quickly implement recommendations to improve your application. Refer to Part 2 of the blog to see how to detect operational issues in Lambda Function automatically with Amazon DevOps Guru for Serverless:
In this blog, we will cover:
- What is Amazon DevOps Guru?
- What makes Amazon DevOps Guru so great?
- With which monitoring services does Amazon DevOps Guru collaborate?
- Features of Amazon DevOps Guru
- Use Cases of Amazon DevOps Guru
- How does it work?
- Pricing of Amazon DevOps Guru
- Companies using Amazon DevOps Guru
- What is Amazon DevOps Guru for Serverless?
- What kinds of issues can Amazon DevOps Guru for Serverless identify?
- Benefits of Amazon DevOps Guru for Serverless
- Conclusion
What is Amazon DevOps Guru?
Amazon DevOps Guru is a machine learning power service that assists you in improving the operational performance and availability of your application by detecting anomalies that are outside of normal operating patterns.
What makes Amazon DevOps Guru so great?
- Amazon DevOps Guru is intended to save you hours, if not days, of time and effort spent detecting, debugging, and resolving operational issues, allowing you to monitor complex and evolving applications more effectively.
- It assists in avoiding common monitoring oversights and errors, such as missing alarms, which cause application downtime.
- DevOps Guru saves debugging time by retrieving relevant and specific information from a large number of data sources when operational issues arise.
- DevOps Guru generates operational insights to notify you of the problem, including a summary of related anomalies, contextual information about why and when the problem occurred, and recommendations on how to resolve issues and reduce application downtime.
With which monitoring services does Amazon DevOps Guru collaborate?
Initially, Amazon DevOps Guru can utilize information from:
- Amazon CloudWatch
- AWS Config
- AWS System Manager OpsCenter
- AWS CloudFormation
- AWS X-Ray
- Amazon DevOps Guru works with partner operations monitoring and incident management solutions such as Atlassian OpsGenie and Pager Duty.
Features of Amazon DevOps Guru
- Consolidate operational data from multiple sources: Amazon DevOps Guru eliminates the need for multiple tools by continuously analyzing and consolidating streams of operational data from various sources, including Amazon CloudWatch metrics, AWS Config, AWS CloudFormation, and AWS X-Ray. It then gives you a single-console dashboard to look for and visualize anomalies in your operational data.
- Save time with ML-powered insights: By using ML-powered recommendations, Amazon DevOps Guru increases application availability and resolves operational issues more quickly and with less manual work. To determine the typical limits of application behavior, it continuously ingests and analyses metrics, logs, events, and traces.
- Automatically configure alarms: For their applications, developers and operators can enable Amazon DevOps Guru to configure and set alarms. DevOps Guru automatically recognizes the new resources and ingests pertinent metrics and logs as applications change and you add new services.
- Detect the most critical issues with minimal noise: In order to provide precise operational insights for critical issues that affect applications, Amazon DevOps Guru draws on years of experience running widely used applications like Amazon.com and uses ML models trained on internal AWS operational data.
- One-click deployment, with no additional software to deploy and manage: You can enable Amazon DevOps Guru on a single account with a single click in the AWS Management Console or a single API call. Through integration with AWS Organizations, Amazon DevOps Guru also supports multi-account insight visibility. Once turned on, Amazon DevOps Guru employs ML to automatically gather and examine information like application metrics, logs, events, and behaviors that deviate from standard operating patterns. There are no extra services to set up or oversee.
- Integrate with AWS services and third-party tools: To find and track connections and dependencies between application components, Amazon DevOps Guru natively integrates with Amazon CloudWatch, AWS Config, AWS CloudFormation, and AWS X-Ray on the AWS cloud computing platform. Additionally, AWS Systems Manager and Amazon EventBridge are integrated with DevOps Guru.
Use Cases of Amazon DevOps Guru
- Improve availability and performance of serverless applications: Detect early signs of serverless application operational issues and resolve them before they affect your customers.
- Reduce recovery time for Amazon RDS databases: In Amazon RDS, you can detect, assess, and resolve a wide range of database-related issues.
- Scale and maintain availability: Automatic updates to static rules and alarms save time and effort, allowing you to effectively monitor complex and evolving applications.
- Proactively identify resource limits: Receive notifications when the provisioned capacity of exhaustible resources such as memory, CPU, and disc space is exceeded.
How does it work?
Pricing of Amazon DevOps Guru
You only pay for what you use with Amazon DevOps Guru. There is no minimum fee or up-front commitment. DevOps Guru begins analyzing operational data for the resources that these applications use after you enable it and specify the applications you want to monitor. Your bill is composed of two components: charges for AWS resource analysis and charges for DevOps Guru API calls. To learn more about the costs of these two components, visit pricing of Amazon DevOps Guru.
Companies using Amazon DevOps Guru
HCL
“We are always looking for ways to reduce the amount of time our teams spend on resolving operational issues, and we are now using Amazon DevOps Guru and leveraging its ML-powered insights to help us identify, correlate, and remediate operational issues quickly. With the insights Amazon DevOps Guru provides, our teams can now quickly find issues without having to start from scratch trying to root cause problems. Our IT team has significantly reduced our mean time to recovery (MTTR), and they are saving hours upon hours of time resolving issues—all the while ensuring our customers have the best end-user experience possible.”
– Anchal Gupta
Senior Technical Lead, DevOps
NextRoll
“We run thousands of EC2 instances and I am always looking for ways to reduce the time my team spends on resolving operational issues. We are excited to use Amazon DevOps Guru and leverage its ML-powered insights to help us identify, correlate and remediate operational issues. This will help my team save hours and reduce our mean time to recovery (MTTR).”
– Valentino Volonghi
CTO at NextRoll
SmugMug
“My team follows an ops-for-life motto, and we are always on the lookout for ways to automate our manual activities. With Amazon DevOps Guru, we hope to realize that goal and let AIOps take over many of our day-to-day tasks, so my team can focus on IT innovation. We are now not only meeting the needs of the business but able to exceed them since we have more time to focus on what matters most – delivering value for our organization and our customers.”
– Andrew Shieh
Operations Director at SmugMug
Presidio
“Many of our customers turn to Presidio and AWS for help flipping the script on traditional IT. Most businesses spend 80% of their technology effort “keeping the lights on” and only 20% on improving engineering practices, pursuing new market opportunties, and enriching end user experiences. With Presidio’s AWS development and engineering expertise and DevOps Guru’s ability to automate tremendous manual effort, we are able to help customers focus less on day-to-day operation and more on value creation.”
– Kyle Hines
VP-Strategic Accounts at Presidio
Belle Fleur
“DevOps Guru is one of our favorite new additions of fully managed AWS services that we have added to AWS solutions in our service catalog. The service is a true value add for our customers saving countless hours as DevOps Guru is trained to analyze logs, metrics, and events across 25 AWS resources. It is very helpful for ourselves as well as our clients that have solutions on AWS as DevOps Guru delivers insights to anomalies in code releases that include details about the impact of problems, as well as how to remediate them.”
– Tia Dubuisson
Co-Founder and President of Belle Fleur
What is Amazon DevOps Guru for Serverless?
Amazon DevOps Guru for Serverless is a machine learning (ML)-powered service that is available for serverless applications that use AWS Lambda. To improve an application’s operational performance and availability, the service employs ML models informed by years of Amazon and AWS operational excellence.
You can use DevOps Guru as a developer or DevOps engineer to automatically detect anomalous behavior at the function, resource, or aggregate levels, and correlate anomalies across resources into a single issue. When DevOps Guru detects an issue, such as low provisioned concurrency capacity for a Lambda function, it combines the relevant metrics, logs, and events that caused the anomaly into a single operational insight and provides intelligent recommendations to help you quickly resolve the problem. In addition, the service provides proactive insights and recommendations to assist you in avoiding operational issues that may affect your application in the future.
You can monitor your serverless applications for performance and operational issues with DevOps Guru—no manual setup, ML expertise, or deep serverless expertise required.
What kinds of issues can Amazon DevOps Guru for Serverless identify?
DevOps Guru for Serverless employs machine learning to correlate anomalies in metrics and logs with operational events and provides contextual insights to assist you in focusing on the appropriate remediation steps.
Furthermore, DevOps Guru for Serverless detects potential issues early on, allowing you to mitigate them before they affect your applications. Proactive insights are classified into three types:
- Resources configuration: Amazon DevOps Guru for Serverless detects that the application’s resources are not configured in accordance with AWS best practices. Consider a Lambda-powered application with an API Gateway endpoint. The Lambda function has more invocations than the currently available function concurrency. This causes continuous spillover of requests, resulting in cold starts, degraded latency, and potentially higher costs. DevOps Guru detects this issue and recommends increasing the provisioned concurrency of Lambda functions.
- Resource exhaustion: Amazon DevOps Guru for Serverless detects that, based on application usage trends, some resources are at risk of being depleted. An Elastic Search node, for example, has a slow memory leak that has been steadily increasing. DevOps Guru detects this and predicts that memory will soon reach its maximum capacity limits, so it generates a Proactive Insight recommending memory cleanup.
- Underutilized resources: Amazon DevOps Guru for Serverless detects that the application’s resources are underutilized. For instance, the DynamoDB for an application may have provisioned write capacity units that are significantly greater than what is actually consumed. DevOps Guru detects this and advises reducing DynamoDB’s provisioned write capacity.
Benefits of Amazon DevOps Guru for Serverless
- Proactively identify and address operational issues: Use DevOps Guru for Serverless to proactively detect application issues and receive recommendations to help correct and rectify the problem before it affects customers. These proactive insights are generated by analyzing operational data and application metrics with machine learning algorithms that can detect early warning signs of future operational issues.
- Optimize application performance: DevOps Guru integrates with Amazon CodeGuru Profiler, allowing you to more easily trace application performance issues to the underlying code and resolve issues more quickly.
- Easily deploy and integrate with AWS services and third-party tools: DevOps Guru can be activated for your serverless applications with a single click in the AWS Management Console or a single API call. When the service detects a problem, it reports it in the DevOps Guru console and sends notifications via Amazon EventBridge and Amazon Simple Notification Service (SNS). You can then automatically manage and respond to operational issues in real-time before they become customer-impacting outages.
Conclusion
In this blog we explored, what is Amazon Devops, what makes it great, its features & use cases, with which monitoring services it collaborates, how does it work, its pricing, and companies using Amazon DevOps Guru. Then we saw Amazon DevOps Guru for Serverless, the issues it helps to identify, and its benefits. In Part 2 of the blog, we demonstrated how to detect operational issues in Lambda Function automatically with Amazon DevOps Guru for Serverless. We will come up with more such use cases in our upcoming blogs.
Meanwhile…
If you are an aspiring DevOps Engineer and want to explore more about the above topics, here are a few of our blogs for your reference:
- How to become a successful AWS DevOps Engineer?
- AWS developer tools to build CI/CD pipeline
- Roadmap To Become A Successful MLOps Engineer
Stay tuned to get all the updates about our upcoming blogs on the cloud and the latest technologies.
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