Big Data Applications Come with Big Expectations
Are you ready to manage big data in production?
Application Performance Management is now available for Big Data
As enterprises continue to scale their use of big data, Unravel is leading the market to meet the needs of business and operations teams to ensure application reliability, optimize storage and compute while minimizing infrastructure costs, and optimize productivity.
Learn how to maximize the performance of big data applications across all your jobs, queries, workflows, pipelines, stages, etc.
Read the blog, Maximize big data ROIBig Data applications need production-grade performance management
Enterprises look to big data applications (e.g., ETL offload, Business Intelligence, Analytics, Machine Learning, IoT, etc.) to drive strategic business value.
As big data applications move to production, performance becomes mission critical.
Ensuring that performance is managed in a unified approach across all the components of the big data architecture is key.
Applications
- ETL Offload
- Analytics
- Machine Learning
Performance Needs
- Meet Deadlines
- Response Time
- Reliability
Key Roles
- Dev: Manage Application
Ops: Manage Cluster Performance
- Data Platform Architect
“Scaling Hadoop from small, pilot projects to large-scale production clusters involves a steep learning curve in terms of operational know-how that many enterprises are unprepared for.”
Read the blog, Gartner market guide for Hadoop operations providersCurrent approach to performance monitoring and management isn’t production-grade
Deploying a big data architecture and infrastructure for Hadoop, Spark, Kafta, etc. is complex.
Managing performance cannot scale because monitoring and troubleshooting tasks are fragmented across logs, graphs, and tools.
Even with management tools like Cloudera Manager, Ambari, MapR Control System,etc., the process to resolve performance issues cannot scale.
PLAN
moreOperations can't plan
Lack of visibilityLack of understanding
Guesswork
RESOLVE
moreOperations react to problems
Escalating trouble ticketsManual troubleshooting
Trial-and-error resolution
MANAGE
moreOperations is flying blind
Lack of controlLack of self-service
Lack of governance
Without production-grade application performance management operations teams cannot meet business needs
LACK OF RELIABILITY
Missed Service-Level-Agreements (SLAs) and Revenue
INEFFICIENT RESOLUTION
High Mean-Time-To-Resolution (MTTR)
SUB-OPTIMIZED RESOURCES
High Infrastructure and Projected Costs
Learn about the most common issues that plague DevOps to manage performance across Hadoop, Hive, MapReduce, Spark, Impala, Kafka, etc.
Read the blog, Top big data performance and operations issuesUnravel delivers production-grade performance management for big data applications
Unravel takes an application-first approach that creates a correlated view of all the performance KPIs across the big data stack.
Unravel also provides automated insight into the root causes of issues as well as recommendations to fix them.
Unravel makes it simple to plan and manage performance because it provides full visibility into utilization and how to optimize every layer of the stack.
PLAN
moreGet a 360-degree View
Smart alerts
Full visibility
Reports
RESOLVE
moreProactive Operations
Auto actions
Automated root cause analysis
Automated recommendations
MANAGE
moreFull Stack Visibility
“MRI” view of the stackOptimize resources
Forecast demand
Unravel meets business needs for performance management of big data applications
GUARANTEE RELIABILITY
Detect and resolve issues across your big data infrastructure, platforms, and applications.
IMPROVE PRODUCTIVITY
Stop wasting time going through graphs and logs & using trial-and-error techniques.
REDUCE COST
Eliminate wastage and poor resource allocation across your infrastructure.
Learn how to quickly resolve performance issues in production across the full big data stack
Read the blog, How to quickly resolve performance issues