Your application’s health depends on the performance of its underlying infrastructure. Unexpectedly heavy processes can deprive your services of the resources they need to run reliably and efficiently, and prevent other workloads from executing. If one of your applications is triggering a high CPU or RSS memory utilization alert, the issue has likely occurred before.
Snowflake is a cloud-native data platform that enables users to easily store, manage, analyze, and share high volumes of structured and semi-structured data. Whereas traditional data architectures often consist of multiple databases, data warehouses, and data lakes, Snowflake breaks down the silos between your different data sources and serves as a single source of truth for a wide range of simultaneous workloads.
Sleuth is a deployment tracking tool that gives you a deeper level of insight into your CI/CD workflows by tracking all of your team’s deployment tools from a single dashboard. Sleuth integrates with different components of your deployment pipeline and develops an understanding of your development processes. It can then automatically alert you as to when code is shipping, when manual approvals are needed, and when failures occur.
Amazon Route 53 provides DNS and traffic routing services for cloud applications. You can use Route 53 to define multiple routing policies to send requests to a variety of endpoints, and configure DNS health checks to re-route traffic for failover, ensuring high availability of your services.
Serverless architectures remove the need to provision and maintain infrastructure components like servers and containers, so developers can focus on writing and deploying code. However, serverless architectures also introduce new challenges to monitoring and observability. Teams building serverless applications can iterate quickly and deploy frequent code and configuration changes, making it difficult to track what impact these changes have on your applications.
Datadog has a long-standing commitment to open standards. Our integrations with OpenMetrics, JMX, and WMI, as well as our implementation of the tried-and-true StatsD protocol, enable you to collect data with the tools and libraries that fit best into your workflows.
Using open source code makes it easier to build applications, but the freely available nature of open source code introduces the risk of pulling potential security vulnerabilities into your environment. Knowing whether or not customers are actually accessing the vulnerable parts of your application is key to triaging security threats without spending hours fixing an issue that doesn’t affect end users.
Tracing is a critical part of monitoring application performance, especially as organizations shift to deploying services using distributed systems, serverless computing, and containerized environments. Teams need real-time, end-to-end visibility into all of the traces relevant to performance issues such as an application outage or an unresponsive service, but managing tracing costs often results in gaps in valuable tracing data.
Logs provide valuable information for troubleshooting application performance issues. But as your application scales and generates more logs, sifting through them becomes more difficult. Your logs may not provide enough context or human-readable data for understanding and resolving an issue, or you may need more information to help you interpret the IDs or error codes that application services log by default.
Terraform is an increasingly popular infrastructure-as-code tool for teams that manage cloud environments spanning many service providers. New users are often drawn to Terraform’s ability to quickly provision compute instances and similar resources from infrastructure providers, but Terraform can also manage platform-as-a-service and software-as-a-service resources.
