4-best-practices-for-software-testing-with-vmware

When it comes time to test your software in VMware, what are the best practices? As it turns out, there is probably already a solution for any issue you might be having. If you happen to stumble across an unusual problem, you can always turn to the vast resources of the VMware community. Here are some of the best practices when it comes time to test your software.

1. Tracking Down Issues You Can’t Recreate

Software Testing

When it comes time to diagnose an issue, it can often be hard to recreate the problem so that you can see what’s going on and get it fixed.

One of the most frustrating parts of testing a new software system is when you encounter an error but you can’t reproduce the problem. In many cases, the bug causes a complete crash, but there is no way to get vital information on what led up to the crash so you can track down and fix the problem. Often, there are multiple bugs that lead to what looks like a single issue, further complicating the matter.

The solution to optimize Software testing is using Record and Replay using VMware Snapshots. This allows you to go back and view the entire VM execution that leads up to an error or crash. You can see all of the threads and processes to find out what triggered the issue. The recorded session is saved in a file for easy access and viewing, even if the error was fatal.

2. Solving Resource Collisions During Testing

When you can’t run different kinds of tests in the same environment due to problems with resourcing, you can solve the problem using cloning and network fencing. You can deploy multiple identical environments at the same time, using one for user acceptance testing, another for regression and integration testing, and still another for installation and upgrade testing.

3. Getting Control When the Test Matrix is Becoming Hard to Manage

When you start having to make tough trade-offs among your test matrix, the schedule for software release, and the quality of software you’re going to put out there, it’s time to get control of the situation. You can do this by creating templates. For example, you can establish Level One as the operating system, Level Two as the operating system plus patches, and Level Three as the operating system plus patches plus apps. Run your tests at Level Three.

4. Use Smart VMware Monitoring

VMware monitoring

VMware environments are a lot like pets and babies. They’re supposed to be okay in there, but you still monitor them at all times, anyway.

Once you deploy your new software, you’ll need to continue to keep an eye on the environment. This means a good VMware monitoring solution. The right monitoring solution can mean the difference in spending all your time babysitting your current applications or actually being able to delve into new developments you’ve been putting off. Opvizor is the ideal solution for monitoring your VMware environment  without having to be so hands-on all the time.

Snapwatcher is a great way to capture VMware snapshots and stay on top of your VMware environment. You can sign up for Snapwatcher here today.

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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.

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