Operations | Monitoring | ITSM | DevOps | Cloud

Earlier this year we released our report on the cost of cloud. Through this white paper we discovered the complexities of cloud costs for businesses and alternatives beyond the hyperscalers. This white paper saw 1,000 cloud developers surveyed about the management of their cloud services, and the degree of costs associated with it. From this analysis, we were able to come up with 5 key takeaways outlining the degree to which hyperscalers are overpromising and under-delivering.

Distributed caching is an important aspect of cloud based applications, be it for on-premises, public or hybrid cloud environments. It facilitates incremental scaling, allowing the cache to grow and incorporate the data growth. In this blog we will explore distributed caching on cloud and why it is useful for environments with high data volume and load.

As cloud technology has matured, hybrid and multi-cloud approaches have become commonplace. Enterprises have discovered that not all applications are suitable for the public cloud, meaning on-premise data centres are still active, and each public cloud has its own strengths and weaknesses, driving businesses to mix-and-match to suit their needs. This results in interoperability challenges for multi-cloud environments.

Enterprises today want real-time business insights to make decisions that improve operational efficiency and customer engagement and present newer revenue opportunities. However, the promise of the data-driven business falls short due to gaps in data management. These gaps exist because data in the modern enterprise doesn’t exist only behind firewalls and within organizational premises.

Amazon Web Services (AWS) provides three types of Elastic Compute Cloud (EC2) instances; On-Demand Instances, Reserved Instances (RIs), and Spot Instances. EC2 On-Demand instances are the default and most expensive instances. RIs and Spot instances offer discounts of up to 72% and 90% on On-Demand instances, respectively. The Reserved Instances are long-term commitments that guarantee you compute power for a year or three. Spot instances fluctuate in price and availability constantly.

Today I will talk about naming convention because I think this is so critical to implement from day one, and people tend to forget. We earlier addressed the importance of providing a good naming convention to your Logic App name and actions inside your business process. Today we will speak about the Connectors (or API Connections) naming convention.

Even though NoSQL databases like Amazon’s own DynamoDB are very popular today, for many business use cases, there’s almost no way around using a traditional relational database. Amazon Relational Database Service (RDS), released back in October 2009, is one of Amazon’s first cloud services and can therefore be seen as a very mature service.

MEGA cloud storage launched in 2013 as a successor of a now-defunct file hosting service Megaupload. It quickly grew to a cloud storage behemoth by making itself stand out by good zero-knowledge and easy-to-use cloud storage equipped with end-to-end encryption. Like its predecessor Megaupload, MEGA is synonymous with internet culture and file storage for many users worldwide.

Debugging application performance in Azure AppService is something that’s quite difficult using Azure’s built-in services (like Application Insights). Among some of the issues are visualizations, and the time it takes to be able to query data. In this post, we’ll walk through the steps to ingest HTTP Access Logs from Azure AppService into Honeycomb to provide for near real-time analysis Access Logs.