Feature Spotlight: Dynamic Dashboard
We recently released the Lumigo Dynamic Dashboard to help our customers visualize metrics to monitor their environment the way they want.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on Serverless Monitoring, Management, Development and related cloud technologies.
7 Reasons Why You Should Consider a Data Lake
With the volume, velocity, and variety of today’s data, we have all started to acknowledge that there is no one-size-fits-all database for all data needs. Instead, many companies shifted towards choosing the right data store for a specific use case or project. The distribution of data across different data stores brought the challenge of consolidating data for analytics.
Microservices vs. Serverless Architecture
Microservices and serverless are both important topics in the world of cloud-native computing. Yet, although serverless functions and microservices architectures often go hand-in-hand, they’re distinct technologies that fill different roles in modern software environments. Here’s an overview of what microservices and serverless are, how they relate to each other, how they are different, and why you may or may not wish to deploy a serverless microservice.
Webinar: Understanding Serverless Observability with AWS and Lumigo
Serverless experts from AWS and Lumigo go over how to add monitoring, logging, and distributed tracing to your serverless applications. Learn how to track serverless health metrics by getting visibility and alerts on specific serverless issues. Then troubleshoot using visual serverless maps, correlated AWS services, and logs to understand what service requires attention to keep high levels of application reliability.
Sumo Logic extends support for OpenTelemetry to AWS Lambda
Cloud-native and serverless come hand in hand. One of the initial motivations to move business workflows to the cloud was related to cutting costs related to provisioning infrastructure and elasticity that on-demand allocation of resources is offering.
Hello, Stack.new
I’ve learned a lot about serverless in my first full year at Stackery after joining from the Ops-focused automation company, Puppet. I’ve learned how to deploy rich CMS-backed web applications in a serverless way, how to cast incantations using CloudFormation’s intrinsic functions, but most of all I’ve learned that there’s a lot to learn in order to be successful in AWS.
Serverless for the Enterprise
Mutual of Enumclaw, a 100-year-old insurance company from Washington, modernized their policy processing system in order to reduce TCO and focus on their software and customers - not infrastructure. However, they realized serverless development still presents many DevOps challenges like environments, workflows, documentation and local development.
Webinar: How Serverless is Changing the Cost Paradigm
-One of the key characteristics of serverless components is the pay-per-use pricing model. For example, with AWS Lambda, you don’t pay for the uptime of the underlying infrastructure but just the number of invocations and how long your code actually runs. This removes the need for many micro-optimizations. As a result, many applications would run at a fraction of the cost if they were moved to serverless.
Move Messages From One Topic Subscription to Another | Serverless360
We are back with an exciting customer’s use case to move messages from one topic subscription to another subscription. Do you wonder, is this is a valid use case? This video discovers the actual business scenario behind this operational need and how Serverless360 can pitch in and meet the requirement.
Using observability to scale AWS Lambda [Live session]
How to utilize observability to optimize your Lambdas for scale and maintain their performance over time - from development to production to scabability. How do you spot potentially slow-running Lambda functions and how do to power-tune them in development? Load testing and how you need a good observability tool for when you do load testing? How to do load testing? How to use observability and make crucial data available in production and at scale? Observability best practices and common mistakes.