Operations | Monitoring | ITSM | DevOps | Cloud

Function as a service (FaaS) offerings like AWS Lambda are a blessing for software development. They remove many of the issues that come with the setup and maintenance of backend infrastructure. With much of the upfront work taken out of the process, they also lower the barrier to start a new service and encourage modularization and encapsulation of software systems. Testing distributed systems and serverless cloud infrastructures.

Here’s everything you need to know to get started with Dashbird – the complete solution for End-to-End Infrastructure observability , Real-time Error Tracking, and Well-Architected Insights. When working with AWS, One cannot emphasize enough the architectural best practices for designing workloads. One of those best practices is to design the solution in such a way that the monitoring of infrastructure and troubleshooting of errors and problems is achieved effortlessly.

Telegraf is one of the coolest open source agents for collecting metrics. It’s part of the TICK Stack (Telegraf, Influx, Chronograf and Kapacitor) and with Telegraf you can collect metrics from a wide array of inputs and write them into a wide array of outputs. It is plugin-driven for both collection and output of data so it is easily extendable.

Serverless event-driven architectures are composed of AWS Lambda functions that regularly interact with databases, APIs, message queues, and other resources to facilitate complex workflows and functionalities. It is therefore crucial to monitor every component of your stack to ensure your applications perform optimally at scale. But traditionally, telemetry data for AWS resources has lived in silos, making it difficult to quickly get the context you need to debug issues.

As a startup, we always want to focus on the most important thing — to deliver value to our customers. For that reason, we are a huge fan of the serverless options provided by AWS (Lambda) and GCP (Cloud Function) as these allow us to maintain and quickly deploy bite-size business logic to production, without having to worry too much about maintaining the underlying servers and computing resources.

Towards the end of 2016, it all started with developing a simple platform to manage Microsoft Azure Service Bus namespaces. The then classic Azure portal had limited capabilities to manage Azure Messaging resources like Service Bus Queues and Topics. Paolo Salvatori developed and managed a community tool called Service Bus Explorer. We identified that there are challenges or limitations in managing and monitoring Azure Messaging resources using the above two.

AWS Simple Storage Service (S3) is by far the most popular service on AWS. The simplicity and scalability of S3 made it a go-to platform not only for storing objects, but also to host them as static websites, serve ML models, provide backup functionality, and so much more. It became the simplest solution for event-driven processing of images, video, and audio files, and even matured to a de-facto replacement of Hadoop for big data processing.

We are in a fantastic era of Application Development. Cloud computing is one of the essential adoptions of today. Enterprises solve their complex problems by designing and building Business Applications using Microsoft Azure offerings like Service Bus, Logic Apps, Function Apps, Event Hubs, Relays, Event Grids. Choosing Microsoft Azure offerings to implement a business solution has significant benefits. That sounds fantastic!