1. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG Big Data Challenges in Application Performance Management Tilmann Rabl Hans-Arno Jacobsen Serge Mankovskii XLDB Conference 2011

2. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Abstract 2 Modern Web Data Platforms (WDPs) handle large amounts of data and activity through massively distributed infrastructures. To achieve performance and availability at Internet scale, WDPs restrict querying capability, and provide weaker consistency guarantees than traditional ACID transactions. The reduced functionality is sufficient for many web applications. High data and query rates also appear in application performance management (APM). APM has similar requirements like current web based information systems such as weaker consistency needs, geographical distribution and asynchronous processing. At the same time, APM has some unique features and requirements that make previously published research and existing architectures inapplicable.

3. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Application Performance Management Enterprise system architectures ▫Very complex distributed systems ▫Need of detailed monitoring ▫Service level agreements Application performance management ▫How many transactions fail? ▫Where is the root cause of failure? ▫What is the end to end response time? ▫Which component is the bottleneck? ▫Which and how many transactions are there? 3

4. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Enterprise System Architecture 4 Client Web Server Application Server Database Client Web Service Main Frame 3 rd Party Identity Manager SAP Message Broker Message Queue

5. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org JSR – 163 JVM is augmented with agent Agent can run additional code ▫No change of code base ▫Trace transactions ▫Measure response times ▫Other types of measurements Huge number of events ▫Potentially for every method invocation JVM Java Byte Code Instrumentation 5 Agent Events Program Additional Code

6. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org APM Performance Requirements High insert rates ▫Millions inserts / sec High query rates ▫Thousands queries / sec Write ratio: >99 % Agents send data in bulks ▫Different periods (seconds to minutes) Big data ▫250 Bytes per record ▫~ 250 MB / sec ▫~ 600 TB / month 6

7. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org MADRID Project Current system’s performance ▫YCSB results < 15K ops / sec ▫TPC-C results ~ 500K transactions / sec Need for a new architecture ▫Massive Asynchronous DistRIbuted Data ▫Highly scalable ▫High write throughput ▫Apart from measurements data mostly static ▫Static queries  Hybrid key-value store 7

8. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Entry Log In-Memory Storage Disk Storage MADRID Architecture Materialized Views ▫Static queries ▫Filters ▫Notifications Hybrid data store ▫All nodes are equal ▫DHT style inserts ▫Replication for static data Asynchronous processing 8 View Manager Message Broker

9. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Schema Excerpt Transaction types ▫No instances ▫Graph structure Metric per transaction ▫Type of measurement Measurements ▫Per transaction type ▫Per metric type ▫Can be aggregations 9 Measurement value min_value max_value no_points start_time end_time metric_id Metric metric_id metric_type transaction_id Transaction transaction_id Transition transaction_id head_component tail_component Component component_id machine description Transaction_name

10. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Materialized Views I What is the average runtime of transaction XY? 10 SELECT transaction_name, AVG(end_time - start_time) FROM Measurement ms, Metric mt, Transaction t WHERE ms.metric_id = mt.metric_id AND mt.transaction_id = t.transaction_id AND mt.metric_type = “runtime_metric” AND ms.start_time BETWEEN “18/10/2011” AND “19/10/2011” AND t.transaction_name = “XY”

11. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Materialized Views II What is the average runtime of transaction XY? 11 Measurement value min_value max_value no_points start_time end_time metric_id Metric metric_id metric_type transaction_id Transaction transaction_id Transition transaction_id head_component tail_component Component component_id machine description AVG_Runtime transaction_id Transaction_name transaction_name metric_id avg_value time_frame

12. MIDDLEWARE SYSTEMS RESEARCH GROUP MSRG.ORG XLDB'11 - (C) 2011, Middleware Systems Research Group, msrg.org Contact Tilmann Rabl ▫University of Toronto ▫tilmann@msrg.utoronto.catilmann@msrg.utoronto.ca Hans-Arno Jacobsen ▫University of Toronto ▫www.msrg.orgwww.msrg.org Serge Mankovskii ▫CA Labs ▫mankovskii@ca.commankovskii@ca.com 12