Having just passed the 10-year anniversary of Malcolm Gladwell’s bestseller “Outliers: The Story of Success“, we thought to mark the occasion by taking a look at outliers and how they relate to success in the business world. Gladwell describes outliers as “those [people] who have been given opportunities — and who have had the strength and presence of mind to seize them.” At Anodot, we’ve also made it our mission to spot outliers, albeit of the data variety.

I regularly speak with managed service providers (MSPs) and one of the biggest challenges I hear them share is selling the concept of managed services to prospects. Many small and medium-sized businesses have yet to move past the concept of break-fix—only paying an IT company to fix things when they break. They don’t fully appreciate the value of the proactive approach that is managed services.

As discussed in our previous post, we recently had the opportunity to present some interesting challenges and proposed directions for data science and machine learning (ML) at the 2018 Scale By the Bay conference. While the excellent talks and panels at the conference were too numerous to cover here, I wanted to briefly summarize three talks in particular that I found to represent some really interesting (to me) directions for ML on the java virtual machine (JVM).

Marketing automation for most people probably regards e-mail marketing. But the newsletter is not the only way to use automatic actions for better timing and personalization. Among them, we can list web push notifications – messages that show up when an Internet user visits browser (not necessarily a particular page).

A lot of firms collect massive amounts of data every day (up to billions of events) to improve their security efforts, enhance their business intelligence, and refine their marketing strategies. Their log storage drives are so big that some of them even brag about the size, to show their public and clients how advanced their technologies are.

The fact that you’re reading this suggests that you like to keep on top of what’s new in tech. With anything and everything now being considered “newsworthy”, it can be hard to filter out the articles that are actually relevant to your interests. That’s why if you’re keen to keep yourself up-to-date on the upcoming digital trends and gadgets of 2019, we suggest bookmarking some of these blogs so that all of your desired reading is just a click away.

Kubernetes allows DevOps teams to deploy containerized applications faster and makes managing containers at scale significantly easier. Obtaining visibility into these containerized applications is key to maximizing application/service performance and proactively preventing downtime.

Distributed denial of service (DDoS) is one of the most insidious types of digital attacks that can cause cloud outages. It is typically directed at a specific target, and if done competently, can bring an application or even all network traffic to its knees.

Site reliability engineering (SRE) is Google’s approach to service management where software engineers run production systems using a software engineering approach. It’s clear that Google is unique, and they usually need to tackle software bugs and errors in different and non-conventional ways. But having software engineers doing a job that is traditionally done by professionals with a systems administration background sounds impractical.

In part 1 of this series, we tried to outline what data retention is and why it is needed to overcome increasing requirements for various regulatory standards. As detailed, there are some clear guidelines for organizations to take what we called a “data retention approach for compliance”. In this follow up post, outline some specific technological and procedural challenges you might face as well as some practical guidelines and strategies to overcome them.