Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

Maintain high uptime and performance for your APIs without any overheads using Google Cloud’s API monitoring tools.

These three top cloud providers are used daily by millions of users across the world – but what sets them apart? We take a magnifying glass to the features that matter.

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.