Operations | Monitoring | ITSM | DevOps | Cloud

You may have heard the word “blockchain” floating around quite a lot recently. However, you may be unsure of what it actually means. However, with companies expected to spend $20 billion per annum on blockchain technical services by the end of 2024, it’s time we all got a bit more familiar with it. Below, we will explain what blockchain is and the technology behind it so you can get a better understanding.

High-quality cloud cost allocation has become an existential issue for businesses. In order to get as much out of their (mounting) cloud investments as possible, business leaders need to know how much they’re spending in the cloud, what/who they’re spending it on, and whether there’s a good reason for it. In its ideal form, cost allocation answers all these questions.

I have been building a feature on elmah.io lately that picks up validation results from an external API. Before serverless was a thing, I would probably have done this using a scheduled task or Windows Service using Hangfire or similar. But after having migrated everything to serverless Azure Functions, I wanted a good solution running similarly. Azure Durable Functions turned out as the perfect companion and in this post, I'll show you a possible way to implement polling of an asynchronous API.

Just as there are a handful of stages to describe the financial journey from startup to established company — pre-seed and seed funding, followed by series A, B, and C funding — there are also stages to the process of achieving a healthy understanding of your costs.

One of the key attributes of DevOps and SRE engineers is their ability to meticulously observe and monitor all of their applications. A task which can be achieved more efficiently by centralizing all generated logs to a central endpoint. By centralizing logging, engineers can, at any time, have an accurate overview of all events which take place across their applications, from just one place. Storing logs in an external system also allows companies to ensure compliance with many certifications.

Kubernetes (K8s) packs a ton of benefits as a container orchestration platform. For instance, K8s is big on automation. This includes automating workload discovery, self-healing, and scaling containerized applications. Yet, Kubernetes isn't always production-ready after a few tweaks. This guide shares crucial Kubernetes best practices you'll want to start using immediately to improve your K8s security, performance, and costs. Let’s get to it!

It’s a wrap! From October 24–28, the Pepperdata team attended KubeCon + CloudNativeCon North America 2022, which brought together top engineers and developers from communities centered around Kubernetes and cloud native. With topics ranging from container observability practices to K8s innovations, Pepperdata unveiled the latest offering of its own: Autonomous FinOps for Kubernetes.

In the fast-growing Azure space, it is essential to scale your business as Azure scales up. Azure is cost efficient by providing a pay-as-you-go model, but it is still necessary for enterprise users to undergo a Cost Analysis to keep their budget at stack. Let us consider a scenario, you’re a manager in your organization, and your team has been using Azure for the last several months. It has created multiple resources that cost money.

From our experience handling Azure Service Bus messages, one frequent suggestion we get from the support person is to download messages from Azure Service Bus entities like Queues and Topic Subscriptions. By downloading the messages as a local copy, it becomes easy for them to debug the messages and use it at a later point in time. Basic knowledge of Azure Service Bus messaging entities is a pre-requisite for the better understanding of this feature.

Don’t forget, it’s the hardware that makes the cloud The main issues we see with clients and cloud implementations are that it can be very difficult for them to get a clear idea of what it is they are buying and how well it will perform. While the consumption and billing models are clear, it can still be hard to know how much you will pay each month. But what is hard is predicting exactly what the level of performance you will get. Some of this is inevitable.