The bottom line: Managing your own analytics infrastructure is complex,
time-consuming, and expensive. You may get some of the insights you need,
but you'll also encounter challenges across many areas, including:
1. Operational efficiency and cost, such as keeping a dedicated team of
experts to manage hardware and software installation, configuration,
integration, patching, and backups
2. Performance and availability, especially during peak workload times
3. Scalability, such as capacity planning and scaling clusters for compute
and storage
4. Security and compliance
In this infobrief, we'll explore an easier and more efficient alternative: fully
managed analytics services. We'll demonstrate how these services diminish or
even outright solve the challenges of self-managed analytics. We'll illustrate
the benefits of these services across three common use cases: big data
analytics, log analytics, and real-time analytics. And we'll introduce you to
three fully managed services from AWS that correspond to those use cases:
Amazon EMR, Amazon Elasticsearch Service (Amazon ES), and Amazon
Managed Streaming for Apache Kafka (Amazon MSK).
Your business needs to dedicate its time and resources to innovation, not
operational burdens. By moving to fully managed analytics services, your
entire business can get the fast, deep insights needed to put data at the core
of every decision—while taking the operational overhead off your schedule
and out of your budget.
3
INTRODUCTION
Fully managed analytics in
action
Leading companies are succeeding with fully
managed analytics services today:
• FINRA processes over 150 billion events per
day on Amazon EMR.
• Autodesk monitors and troubleshoots
application and infrastructure issues in near
real time using Amazon ES.
• ZipRecruiter leverages Amazon MSK to allow
its engineers to focus on business-critical tasks
instead of managing infrastructure.
Look for deeper info and more success stories in
similar sections throughout this infobrief.
