How to deploy your models with SAS Model Manager to Hadoop

An important step of every analytics project is exploring and preprocessing the data. This transforms the raw data to make it useful and quality. It might be necessary, for example, to reduce the size of the data or to eliminate some columns. All these actions accelerate the analytical project that comes right after. But equally important is how you "productionize" your data science project. In other words, how you deploy your model so that the business processes can make use of it.


How to Send Data through Logstash or Kafka from Elastic APM

In modern deployments, application servers often have short lifetimes or use less reliable hardware (preemptible/low-priority VMs, spot instances) than other components, like message queues and databases. In those cases, it’s best to get data off to a more reliable system quickly. Starting with the 6.4.0 release, APM Server is able to send data to Logstash or Kafka, offloading the reliability requirements to one of those systems.


In A Digital World Where The Speed of Innovation Matters, Are You Anchored Down by Legacy APM Agents?

In our previous blog, we showed how traditional APM solutions fail to provide reliable visibility into application performance because they rely on head-based sampling. The probabilistic and random nature of head-based sampling was good enough for legacy monolithic applications because of their predictable performance patterns. They ran with code in a single unitary system without being subject to frequent changes.


10 API Testing Tips for Beginners (SOAP & REST)

API (application programming interface) testing is a type of software testing that performs verification directly at the API level. It is a part of integration testing that determines whether the APIs meet the testers’ expectations of functionality, reliability, performance, and security. Unlike UI testing, API testing is performed at the message layer without GUI.


Migrating from Monolithic to Cloud Native Applications

Lately, the public cloud services market has created one of the biggest disruptions in the tech market. In fact, as per Forrester Data, public cloud services forecasted a 22% CAGR in the public cloud market from 2016 to 2020. In addition, Gartner projected the Infrastructure as a Service (IaaS) to grow 35.9% by end of 2018 to reach $40.8 billion. Looking at the potential of the cloud market and the benefits associated, right now would be the apt time to migrate from monolithic to the cloud.


Where Context is King: Beyond Utilization in Asset Management

Organizations need better network oversight. According to Information Week, recent data predicts “wasted” cloud spending on services and applications that aren’t fully utilized will reach $21 billion by 2021, while CIO points to Gartner research that suggests 30 to 40 percent of IT spending in large enterprises is actually funding shadow IT.