Snapt Blog


Why Application Metrics and Monitoring Matter

by Iwan Price-Evans on Performance • August 2, 2022

Applications and services are the backbone of a company's digital ecosystem. They ensure that businesses run smoothly, customers are satisfied, and employees can do their jobs effectively. However, all applications have weaknesses that attackers can exploit to compromise users or steal sensitive data. In addition, every application has an expected level of performance that customers expect; if it falls short of its requirements, users will switch providers.

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Top Use Cases for Machine Learning in Web Applications

by Craig Risi on Business • July 26, 2022

So, you have a web application, and you are considering exploring some machine learning (ML) solutions to see where they can be of value for your business. Well, the industry has already seen a lot of development and research in this space, so there are already many successful use cases that we can look at to see how ML might benefit your particular application.

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What Your Watch (Probably) Says About Your Load Balancer

by Iwan Price-Evans on Load Balancing • July 21, 2022

I recently got into watches. Naturally, I became an insufferable bore almost immediately. It’s a culture and a field of engineering that comes with two centuries of jargon from hairsprings to tourbillons. If you can’t tell your tapisserie dial from your patisserie croissant, you’ll find it pretty impenetrable and exclusive.  So obviously it made me think about load balancers and other app infrastructure.

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Ultimate Guide To Application Security

by Iwan Price-Evans on Tips and Tricks • July 14, 2022

This is the ultimate guide to securing your applications, servers, and APIs, including design, coding, testing, compliance, deployment, infrastructure, and threat intel.  Cyber security is of critical importance: According to a TransUnion Holiday Retail Fraud Survey, 46% of customers are concerned ...

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When To Use Machine Learning (And When Not To)

by Craig Risi on Machine Learning • July 12, 2022

In previous articles, we looked at how machine learning (ML) works and how to choose the right learning model for you. However, just because we can use machine learning, it doesn’t follow that it is always the best solution for any computational problem. So, in this guide, we will look at some of the limitations of ML, when to use it, and when to avoid it.

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How to Monitor Kubernetes Containers

by Dave Blakey on DevOps • June 30, 2022

The introduction of containers has revolutionized the software development industry and made building, testing, and deploying applications significantly easier. However, modern applications and infrastructure require an ever-growing number of containers and servers. These generate such a volume of logs and information that monitoring everything is a massive challenge. Deadlines, inexperience, culture, and management are just some of the obstacles that can affect how successful teams are at overcoming this challenge. 

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