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When building serverless applications on AWS Lambda, Amazon CloudWatch provides out-of-the-box metrics that measure the performance, errors, and duration of your functions. Although these standard Lambda metrics provide visibility into your serverless applications, it can also be invaluable to monitor custom metrics that are unique to your use case and application.
Ciara details how and when to generate an SBoM with the help of open-source tooling. Learn how to host SBoMs, as well as other SBoM considerations.
Modern application deployments rely heavily on containerization for its scalability, availability and ease of maintenance. Legacy applications implemented before the containerization era often use monolithic, hardware-centric architectures that are difficult to scale and manage. These legacy applications may have multiple services bundled into the same deployment unit without a logical grouping.
The first continuous integration (CI) tools were all self-hosted, meaning they ran on a developer’s local computer or server. Although this setup was viewed favorably by dev teams at the time, it has limited flexibility, and developers had to spend time maintaining the infrastructure.
Service level objectives (SLOs) state your team’s goals for maintaining the reliability of your services. Adopting SLOs is an SRE best practice because it can help you ensure that your services perform well and consistently deliver value to users. But to gain the greatest benefit from your SLOs, you need ongoing visibility into how well your services are performing relative to your objectives.