Operations | Monitoring | ITSM | DevOps | Cloud

Thanks to regulation, legislation and the pandemic, the term ‘resilience’ has burst into the consciousness throughout the financial services industry. But why is it so important? To answer this, we are going to delve deeper into the world of Operational Resilience by exploring how it has the potential to deliver a lot more than merely regulatory compliance.

As Charles highlights in his Financial Services Predictions blog, operational resilience is critical. The regulatory drive for defining, measuring and improving operational resilience is clear within Europe, outlined by EU DORA and UK FCA / PRA guidelines. The organisations who embrace this change can capitalise on real opportunities in the coming years; specifically, the opportunity to use data-driven insights to improve customer experience and proactively resolve issues before customer impact.

“How do you know your web properties and APIs are up and functioning as expected for users, not just nationally, but across the entire planet?“ Splunk Synthetic Monitoring provides an effective solution to monitor and track the reliability of web properties from locations all over the globe. By generating simulated user or API requests with Splunk Synthetics you’ll quickly be able to measure response times from various locations, devices, and connection types.

The sooner you know about a problem, the sooner you can address it, right? Imagine if you could do that in your most important apps and software. Well, that’s exactly what MTTA measures. Let’s take a look.

The amount of data organizations handle has created the need for faster data access and processing. Data Denormalization is a widely used technique to improve database query performance. This article discusses data normalization, its importance, how it differs from data normalization and denormalization techniques. Importantly, I’ll also look at the pros and cons of this approach.

In today’s turbulent times, companies big and small are being pushed to do more with less. Budgets are getting tighter and companies are being pressured to serve customers who demand 24/7 availability from their applications and services. To meet these demands and remain competitive, enterprises are adopting cloud-first strategies and developing applications with microservice architectures.

Has the public sector ever been under so much pressure? Universal across all government departments, essential public services are under significant strain. However, COVID-19 and the subsequent knock-on impacts (economic, social and healthcare challenges) have buckled the resilience and kept many front-line concerned with delivering the scale of service required by the public.

As Sean Price discusses in his ‘2023 Public Sector Predictions’ blog, European government departments and agencies are under pressure to reduce costs, improve efficiency and provide a better citizen experience. Governments need to offer more services at higher quality at a time when it costs more to heat buildings and to employ people to run the services.

DevOps teams combine development and operations to boost productivity at work. For this to happen, the professionals must possess the right skills, knowledge of the right tools and the DevOps mindset. This makes it an interesting department to work in as, over time, you’ll be able to build a portfolio of soft and hard skills that will be useful in different spaces.

A data lakehouse is a modern data architecture. It is popular among many organizations that incorporate the features of both data lakes and data warehouses. The features of a data lakehouse make it ideal for a range of data analytics use cases. This article explains data lakehouses, including how they emerged, how they shape up versus data lakes and data warehouses, their architecture, and finally, the pros and cons of using a data lakehouse.