Automated Multi-Tier System Design for Service Availability

Transcription

1 Automated Multi-Tier System Design for Service Availability G. (John) Janakiraman, Jose Renato Santos, Yoshio Turner Internet Services and Storage Laboratory HP Laboratories Palo Alto May 22, 2003

2 Author Information G. (John) Janakiraman and Jose Renato Santos Working in: HP Labs Internet Systems & Storage Group in Palo Alto, California This group is currently designing a new computing model (Planetary computing) to handle the large infrastructure needs required to support the growing Internet.

3 Author Information Yoshio Turner Education: Attended CS program at UCLA Working in: HP Labs Datacenter Architecture Team and the Internet Systems & Storage Lab Current Research Interests Data center server architecture High service availability for services that are hosted on datacenter clusters Interconnection networks routing, congestion, and Quality of Service

4 Grand Vision HP, IBM, and Sun Microsystems are attempting to deliver computing as a utility. The idea is that a user who wishes to deploy an Internet or Enterprise service would issue a request to a computing utility, which in response would automatically allocate and configure appropriate resources from pools of compute, storage, and networking resources to create a secure, virtualized computing environment that realizes the service. (Janakiraman 1)

5 Acronym Review UDC Hewlett Packard s Utility Data Center Commercial solution Recognizes current state of achieving utility vision AVED Proof-of-concept prototype Provides design automation for highly available system infrastructures Improves self-management functionality of UDC

6 Current Practice and Impact of AVED Currently, human system developers manually generate design alternatives for the system. Then, they use availability modeling tools to evaluate the availability of their designs. Modeling AVED automatically Tool Usage generates designs that meet -Predicts availability Service and Downtime performance requirements. -Predicts then the AVED cost of evaluates the downtime them using based the on modeling the business tools. mission -Provides AVED can upper be faster limit than on the system human availability designers in that designing can be achieved. an optimal solution. Plus, AVED could improve the -Provides solution cost-benefit quality by having tradeoffs a wider of the range different of potential design options solutions to evaluate.

7 Components of a Self Managing System High Level Service properties Descriptions Specify Service uptime the failure Throughput properties Mean Tolerable Time Degradation Between Failure Duration (MTBF) met. Specify Bounds the and recovery cost of degradations properties Mean Time to Repair (MTTR) Automated Design Engine Selects and configures infrastructure components and availability mechanisms Ensures that high level requirements are Automatically explores design alternatives and embeds environment models Infrastructure Repository Determines the design alternative that Provides empirical information about: satisfies the requirements at the minimal cost. infrastructure element failure properties transient failure rates, restart times, Automated Deployment and Automated permanent failure rates, and scope Runtime of failures. Management Availability attributes Deploy and configure the availability Identify the infrastructure component, failure Monitoring Infrastructure mechanisms. mode, repair latency, recovery latency, and Monitor failure characteristics Ensure that backup resources are available for impact on service. Monitor recovery characteristics upgrades failure and ensure that they are scheduled dependencies, failure rates, repair when times, business impact is minimal. and recovery times.

8 AVED Architecture Service Description Purposes 1. Provides high level performance requirements Specification currently includes: Minimum acceptable performance Maximum annual downtime 2. Describes the service structure Availability Evaluation Engine The translation module converts the intermediate design representation into an availability model which is inputted into one of the availability evaluation engines. AVANTO, Mobius, and SHARPE

9 Three Tier Structure Example Tier name tiers that are to comprise the service implementation Tier Singleload nmax Cluster Resource Maximum Can Indicates it candidate be number deployed the resources performance of in active a clustered that resources of can a configuration single be used resource in each in in which tier servicespecific spares load are units. active used.

10 Resource Type Definition

11 Hardware Component Specification Cost Failure Repair Preemptive Options Modes Maintenance Annualized For Preemptive each failure maintenance cost mode, for various there can operating can have be an multiple impact modesrepair on perm_mtbf = mean time between permanent failure options. availability. The design selects exactly one for each tran_mtbf = mean time between transient failure cost_cold component. Software rejuvenation = cost if resource can is improve powered MTBF off for a failover_used = failover to an available cold spare cost_active repair_mttr failure mode. = cost mean if resource time to repair is powered on failover_duration = time required for failover repair_cost Future plans = to annualized define PM cost option per parameters. node for repair

12 Design Space Search

13 Designing the Application Tier of an Internet Service for High Availability: Components Failure Behavior and Costs

14 Service Characteristics

15 Optimal Solution

16 Additional Annual Cost Required for Availability

17 Downtime Sensitivity to Repair Time with Cold Spares

18 Downtime Sensitivity to Repair Time with Active Spares

19 Conclusions Since a significant loss of business can result from degraded service availability, service availability management is very important. Research focused on automating service availability management. Requirements must be at a high level Service Description must specify failure, recovery, and repair parameters. Design function must automatically generate design alternatives, build availability models, and evaluate them to select the best design. System must also perform monitoring, deployment, and configuration. These concepts were demonstrated in AVED.

20 Future Plans Addressing overall service availability through examining network and storage system impact Factoring in network topologies (LAN), network application placement, and network failures and recovery. Improving data dependability Making design space richer Database engine configuration parameters Application server configuration parameters Virtual machine usage Software rejuvenation Relaxing restrictions Each tier will no longer need to be homogeneous Tiers will be able to have heterogeneous components Coupling AVED with a UDC environment