sql-server-performance-of-vmware-cloud-on-aws

Please find here the original article from VMware’s performance team or scroll down for more information.

In the past, I’ve always benchmarked performance of SQL Server VMs on vSphere with “on-premises” infrastructure.  Given the skyrocketing interest in the cloud, I was very excited to get my hands on VMware Cloud on AWS – just in time for Amazon’s AWS Summit!

A key question our customers have is: how well do applications (like SQL Server) perform in our cloud?  Well, I’m happy to report that the answer is great!

VMware Cloud on AWS Environment

First, here is a screenshot of what my vSphere-powered Software-Defined Data Center (SDDC) looks like:

SQL Server

Photo courtesy of VMware’s performance team

screenshot shows several notable items:

  • The HTML5-based vSphere Client interface should be very familiar to vSphere administrators, making the move to the cloud extremely easy
  • This SDDC instance was auto-provisioned with 4 ESXi hosts and 2TB of memory, all of which were pre-configured with vSAN storage and NSX networking.
    • Each host is configured with two CPUs (Intel Xeon Processor E5-2686 v4); each socket contains 18 cores running at 2.3GHz, resulting in 144 physical cores in the cluster. For more information, see the VMware Cloud on AWS Technical Overview
  • Virtual machines are provisioned within the customer workload resource pool, and vSphere DRS automatically handles balancing the VMs across the compute cluster.

Benchmark Methodology

To measure SQL Server database performance, I used HammerDB, an open-source database load testing and benchmarking tool.  It implements a TPC-C like workload, and reports throughput in TPM (Transactions Per Minute).

To measure how well performance scaled in this cloud, I started with a single 8 vCPU, 32GB RAM VM for the SQL Server database.  To drive the workload, I created a 4 vCPU, 4GB RAM HammerDB driver VM.  I then cloned these VMs to measure 2 database VMs being driven simultaneously:

SQL Server

Photo courtesy of VMware’s performance team

I then doubled the number of VMs again to 4, 8, and finally 16.  As with any benchmark, these VMs were completely driven up to saturation (100% load) – “pedal to the metal”!

Results

So, how did the results look?  Well, here is a graph of each VM count and the resulting database performance:

SQL Server

Photo courtesy of VMware’s performance team

As you can see, database performance scaled great; when running 16 8-vCPU VMs, VMware Cloud on AWS was able to sustain 6.7 million database TPM!

I’ll be detailing these benchmarks more in an upcoming whitepaper, but wanted to share these results right away.  If you have any questions or feedback, please leave me a comment!

Please find here the original article from VMware’s Performance Team with all comments.

CNIL
Metrics and Logs

(formerly, Opvizor Performance Analyzer)

VMware vSphere & Cloud
PERFORMANCE MONITORING, LOG ANALYSIS, LICENSE COMPLIANCE!

Monitor and Analyze Performance and Log files:
Performance monitoring for your systems and applications with log analysis (tamperproof using immudb) and license compliance (RedHat, Oracle, SAP and more) in one virtual appliance!

Subscribe to Our Newsletter

Get the latest product updates, company news, and special offers delivered right to your inbox.

Subscribe to our newsletter

Use Case - Tamper-resistant Clinical Trials

Goal:

Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance

Goal:

Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

Implementation:

While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

White Paper — Registration

We will also send you the research paper
via email.

CodeNotary — Webinar

White Paper — Registration

Please let us know where we can send the whitepaper on CodeNotary Trusted Software Supply Chain. 

Become a partner

Start Your Trial

Please enter contact information to receive an email with the virtual appliance download instructions.

Start Free Trial

Please enter contact information to receive an email with the free trial details.