In our Data Lake vs Data Warehouse blog, we explored the differences between two of the leading data management solutions for enterprises over the last decade. We highlighted the key capabilities of data lakes and data warehouses with real examples of enterprises using both solutions to support data analytics use cases in their daily operations.

Cloud computing shapes the ability of enterprises to transform themselves and compete in the 2020s. By renting elastic cloud resources, enterprises can support new customer platforms, distributed workforces, and back-office operations. The cross-functional discipline of CloudOps helps enterprises realize the promise of cloud computing by optimizing applications and infrastructure on cloud platforms.

Today’s enterprise networks are heterogeneous, have multiple entry points, integrate with cloud-based applications, offer data center delivered services, include applications that run at the edge of the network, and generate massive amounts of transactional data. In effect, enterprise networks have become larger, more complex, and more difficult to secure and manage.

Last year we published a popular paper on how to calculate the true cost of an Elasticsearch, or ELK (for Elasticsearch, Logstash, Kibana) stack environment. The paper helps readers calculate their overall annual cost of ownership for their ELK environment, and reveals how the cost burden of ELK is much higher than anticipated for most customers. That paper clearly hit a nerve — it’s been, by far, our most downloaded piece of content.

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.

At the turn of the 20th Century, enterprises shut down their clunky generators and started buying electricity from new utilities such as the Edison Illuminating Company. In doing so, they cut costs, simplified operations, and made profound leaps in productivity. The promise of modern cloud computing invites easy comparisons to those first electric utilities: outsource to them, save money and simplify.

The global market for log management was valued at $1.9 billion in 2020, according to MarketsandMarkets. Analysts predict this will grow to $3.7 billion by 2025. With this massive growth in log data, there will also be massive demand for escalated support in log management systems.

If Ben Franklin lived today, he would add cyber threats to his shortlist of life’s certainties. For decades, bad guys have inflicted malware, theft, espionage, and other forms of digital pain on citizens of the modern world. They seek money, celebrity, and political secrets, and often get them. In 2020, hackers halted trading on the New Zealand stock exchange with a distributed denial of service (DDoS) attack.

Exciting news — ChaosSearch won the 2021 InfoSec “Cutting Edge in Cybersecurity Analytics” award from Cyber Defense Magazine! We’re honored to be recognized for our innovation in delivering security insights at scale. The InfoSec panel of judges is made up of certified security pros who understand what SecOps teams care about and how log analytics should be applied to keep data secure.

Properly analyzing the massive amounts of data created by network access and the associated security tools has become a very tedious chore. Today’s cybersecurity professionals are seeking ways to better deal with the massive influx of information so that they can make intelligent choices when it comes to the cybersecurity posture of their networks. Selecting the proper tools is an important task which merits investigation.