Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.
Getting Started with Dashbird
Dashbird is a service to monitor, debug, and improve serverless applications.
Serverless architecture fundamentally changes how we build, deploy, and maintain software. Although AWS CloudWatch can be used to monitor cloud resources, it was not designed for the challenge. Dashbird fills the gaps left by CloudWatch and other traditional tools.
Developers can track the Inventory of cloud components in one single place. This allows for an effective and effortless observability process over the entire serverless cloud stack.
Lambda functions have a special monitoring section, due to the complexity and amount of data generated by execution logs. Differently from AWS CloudWatch, Dashbird individualizes each invocation logs and includes metrics and traces to make it easier to debug any potential issues or performance bottlenecks.
Aggregated metrics are also provided for each function. Detailed statistics include average, minimum, maximum, and 99th percentile. Multiple dimensions are aggregated for each function:
- Memory utilization
These metrics support not only function health analysis but also resource and cost improvements.
Dashbird monitors cloud components in serverless applications and cross-reference against well-architected best practices. Services monitored by Dashbird Insights include SQS queues, ECS containers, DynamoDB tables, API Gateways.
Insights are automatically generated when: git st
- Your infrastructure is likely to fail
- Our system identifies opportunities for improvement
Error Tracking and Alerting
Track errors in real-time and receive proactive alerts by email and Slack whenever issues are detected in your serverless stack.
Dashbird has automated issue detection algorithms so that developers don’t have to worry about what they should monitor. Our system also cross-checks cloud components behavior against well-architected best practices, anticipating risks of failure, and suggesting opportunities for improvement.
Dashbird automatically detects all types of application errors and exceptions, in every runtime supported by AWS Lambda: NodeJS, Python, Java, Ruby, Go, .NET. It also monitors errors related to the Lambda platform and its limits, such as timeout, out of memory error, etc.
Other cloud components also have their own set of monitors. SQS queues are checked for a growing number of pending messages, DynamoDB tables have throttling and resource capacity consumption verified, ECS containers have resource-usage tracked (e.g. memory, CPU utilization level).
Dashbird also integrates with AWS X-Ray, so that Lambda functions logs can be analyzed in connection with application traces and errors in a single interface.
Monitor each function behavior with customized policies based on performance and resource usage.
For example, an incident can be raised when one or more Lambda functions start using more than 90% of memory, on average, and the situation persists for a period of 15 minutes.
Under the Hood your Serverless Stack
Dashbird requires zero instrumentation (no code changes). Lambda costs, execution time, and speed, as well as latency, will not be affected.
In a handful of clicks and less than five minutes, through a CloudFormation stack, we will connect to your AWS account privately and monitor Lambda logs in CloudWatch Log groups. From that on, Dashbird will automatically start monitoring your serverless stack.