Operations | Monitoring | ITSM | DevOps | Cloud

August 2021

Serverless observability and real-time debugging with Dashbird

Systems run into problems all the time. To keep things running smoothly, we need to have an error monitoring and logging system to help us discover and resolve whatever issue that may arise as soon as possible. The bigger the system the more challenging it becomes to monitor it and pinpoint the issue. And with serverless systems with 100s of services running concurrently, monitoring and troubleshooting are even more challenging tasks.

Challenges and Opportunities of Going Serverless in 2021

While we know the many benefits of going serverless – reduced costs via pay-per-use pricing models, less operational burden/overhead, instant scalability, increased automation – the challenges of going serverless are often not addressed as comprehensively. The understandable concerns over migrating can stop any architectural decisions and actions being made for fear of getting it wrong and not having the right resources.

Best practices for collecting and managing serverless logs with Datadog

Logs are an essential part of an effective monitoring strategy, as they provide granular information about activity that occurs anywhere in your system. In serverless environments, however, you have no access to the infrastructure that supports your applications, so you must rely entirely on logs from individual AWS services when troubleshooting performance issues.

Securing Serverless Applications with Critical Logging

We’ve seen time and again how serverless architecture can benefit your application; graceful scaling, cost efficiency, and a fast production time are just some of the things you think of when talking about serverless. But what about serverless security? What do I need to do to ensure my application is not prone to attacks? One of the many companies that do serverless security, Protego, came up with an analogy I really like.

Zero effort performance insights for popular serverless offerings

Inevitably, in the lifetime of a service or application, developers, DevOps, and SREs will need to investigate the cause of latency. Usually you will start by determining whether it is the application or the underlying infrastructure causing the latency. You have to look for signals that indicate the performance of those resources when the issue occured.

Simplifying App Deployments for Developers - A Short History from Timesharing to Serverless

I have been in the IT industry for a few decades now and have helped launch waves of technology in the constant pursuit of making computing easier, cheaper and with greater uptime. This all started well before my entry into the IT industry and will continue to well past the time I retire. However, it is always good to understand where we have been and look how far we have come to understand how we can continue to make it even better.

Serverless with AWS - Image resize on-the-fly with Lambda and S3

Handling large images has always been a pain in my side since I started writing code. Lately, it has started to have a huge impact on page speed and SEO ranking. If your website has poorly optimized images it won’t score well on Google Lighthouse. If it doesn’t score well, it won’t be on the first page of Google. That sucks.

How to Test JavaScript Lambda Functions?

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.

Dashbird Explained: the why, what and how

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.

Running Telegraf as Serverless on AWS Lambda for Monitoring Your Cloud

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.

Monitor your entire serverless stack in the Serverless view

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.

Debugging Cloud Functions

Developing a Cloud Function, but having issues troubleshooting it? In this episode of Serverless Expeditions Extended, we show you how to debug your function locally so you can avoid the risk of testing in production. Watch to learn how you can easily install the Functions Framework, set up the Node debugger, and fix your functions!

My honest review: I tried AWS Serverless Monitoring using Dashbird.io

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.

Introducing the All New Serverless360!

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.

8 Must-Know Tricks to Use S3 More Effectively in Python

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.

Application view for Azure Serverless Integrations

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!

Application view for Microsoft Azure Resources

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!