“Testing your production environment” refers to the practice of running tests on production servers, using actual data from real users. Production testing doesn’t replace other methods like unit or integration testing. Instead, it extends them. Smoke testing is one approach that Lumigo has implemented to test our own production environments.
Managed services and serverless deployments have become increasingly popular tools in the software development process. This means that organizations are focusing less on infrastructure resources and more on the functionality and security of applications. Managed services—such as the applications like DynamoDB, Step Functions and API Gateway that are crucial to serverless architectures—come with associated costs.
Over the past few years, AWS has made incremental improvements to Lambda’s cold start performance. Nowadays, cold starts are much less an issue for most functions, unless you’re using Java or.Net Core.
At Lumigo, we keep improving the coverage and quality of our distributed tracing instrumentation to give you, through Lumigo’s transactions, the most accurate and intuitive representation of how your distributed system behaves. In this blog, we cover a recent development for the Amazon SQS instrumentation in Lumigo’s OpenTelemetry distro for Python, providing a seamless experience for a scenario that otherwise would result in confusing, broken transactions and lost insights.
Back in 2020, we covered the launch of Lambda Extensions and the subsequent release of the Lambda Logs API. These features aren’t designed for the average Lambda user. But they allow vendors to build better tools by giving them much-needed access to the Lambda execution environment.
Amazon CloudWatch monitors metrics of your Amazon Web Services (AWS) resources in real time and can trigger alarms when a metric goes above or below certain thresholds. Typically, Amazon CloudWatch sends out alarms by posting a message to an SNS (Amazon Simple Notification Service) topic, which distributes the message via several mediums, including email, SMS, and Lambda functions. Setting a CloudWatch alarm can be complex.
With serverless and containerized applications becoming a norm, workloads and integrations are spread across multiple cloud environments. As these apps become increasingly more distributed, monitoring also becomes more complicated with siloed and incomplete telemetry. This is where distributed tracing brings great value. It enables end-to-end visibility in your modern and complex application.
The internet of things is one of my favorite topics. IOT enables low-powered connected devices that opens gateways from the digital to the real world. While I love tinkering away with an Arduino sketch and the latest Espressif or Arduino board, there is always an air of frustration when trying to build out what at first seems like simple functionality using one of these “smart devices” because of the limited view we have into their operations.
Lambda is the glue that holds serverless architectures together. Before its release, most users felt it was a matter of luck as to whether AWS would let you connect a service to another. If not, you had to spin up a VM or a container to transform the events from one service in a way that your target service could handle them. Since Lambda was easier to set up, people assumed that all code they would deploy on it would run faster and cheaper than on other compute services.
As a developer, I love the versatility of Python. Over the years I have used Python for so many different use cases: game development, APIs, IoT, machine learning, and web development. It can scale tall applications in a single bound and take on any challenge faster than you can pip install flask. Something you learn very quickly in the world of app development is to build everything for scale.
