Operations | Monitoring | ITSM | DevOps | Cloud

Understand the two dimensions of scaling for database query and ingest workloads, and how sharding can make scaling elastic — or not. Scaling throughput and performance are critical design topics for all distributed databases, and sharding is usually a part of the solution. However, a design that increases throughput does not always help with performance and vice versa. Even when a design supports both, scaling them up and down at the same time is not always easy.

Most engineering teams are no strangers to key performance indicators (KPIs), those metrics tracking progress toward critical goals and targets. Ideally, tech leaders design KPIs to focus teams on what matters and prove their contribution to the company’s overall performance. Of course, KPI data should also uncover critical information that guides informed decision-making. For engineering teams tasked with managing the customer experience, KPIs often track availability.

The drive for faster, more scalable services is on the rise. Our day-to-day lives depend on apps, from a food delivery app to have your favorite meal delivered, to your banking app to manage your accounts, to even apps to schedule doctor’s appointments. These apps need to be able to grow from not only a features standpoint but also in terms of user capacity. The scale and need for global reach drives increasing complexity for these high-demand cloud applications.

Like every business sector, Financial Services has been on a rollercoaster ride over the past couple of years. The pandemic forced a change in the way businesses work, and the way products and services are delivered to customers. Deloitte summed it up beautifully in the introduction to its ‘Finance 2025 Revisited report’1: “COVID-19 has sped up business innovation and stress-tested the concept of 100% remote work.”

A good chunk of your Amazon Web Services (AWS) public cloud spending goes to the Amazon Elastic Compute Cloud (Amazon EC2) service. Because it is the default compute service on AWS, Amazon EC2 is key to building, running, and scaling your AWS-based applications. That also means Amazon EC2 pricing has a tremendous impact on your AWS budget. Understanding how the EC2 billing model works will help you control and optimize your AWS spending.

On 10th December 2021, Apache foundation admitted the Log4Shell vulnerability of its Log4j 2.16 version. Chen Zhao Jun was an Alibaba cloud services security analyst who first found out about this security threat and consequently reported it to the foundation. Upon further investigation, they identified that the vulnerability had existed since 2013. Unfortunately, by then all the corporations, big and small were affected by this malicious security breach.

Docker is a PaaS product, developed by Docker.Inc to containerize applications. It does so by combining app source code with OS libraries and dependencies required to run that code in any environment. Kubernetes is a similar tool developed by Google, which scales up this containerized application after deployment. While one works in building the containers the other essentially helps in scaling it up, then why so much buzz around these two?

The main street in my town is mostly lined with mom-and-pop shops, and I love to support these businesses. Large online retailers keep making it harder for these stores to compete, so I think it’s important to keep doing business with them when I can. Lately, it’s been interesting to see that these mom-and-pop shops increasingly have something in common with the largest online retailers: They’re reliant on the internet to deliver their goods and services to consumers.

We’re extremely happy to announce that Torq has joined the Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining and raising awareness of best practices to help ensure a secure cloud computing environment. The CSA has more than 80,000 members worldwide and has been endorsed by the American Presidential Administration, which selected the CSA Summit as the venue for announcing the federal government’s cloud computing strategy.

Designing a production service environment around Apache Kafka that delivers low latency and zero-data loss at scale is non-trivial. Indeed, it’s the holy grail of messaging systems. In this blog post, I’ll outline some of the fundamental service design considerations that you’ll need to take into account in order to get your service architecture to measure up. Let’s start with the basics.