pure-storage-multipathing-and-best-practices

As we´re also using Pure Storage in our own production environment, we wanted to check for best practices using it. As we´re eating our own dog food, first thing was of course analyzing our own environment with our Health Analyzer. Ouch that hurts – lots of issues in our own environment… wrong or non-optimized multipathing set for some datastores. Looking deeper into it, we found out that we were using out of the box MRU (most recently used). This is the VMware vSphere default, when connecting the Pure Storage as Storage Array Type Plugin (SATP) VMW_SATP_ALUA is chosen automatically.

Pure Storage  default multipathing

As we just started using Pure Storage for some weeks, we didn´t optimize the environment in the beginning. But now was the right time.

Pure Storage Round Robin multipathing

Therefore we made the simplest and most important change for stability and performance – Pure Storage Multipathing policy should be Round Robin. Important to know, if you don´t change the default setting in the VMware ESXi configuration you need to change this setting for each datastore on all hosts.

Pure Storage Multipathing - all pathes used

After setting all ESXi Hosts and datastores correctly the performance is even better and all pathes are used! Of course you can further tune these settings changing the I/O treshold.

A very nice guide about Pure Storage multipathing and more best practices from Cody Hosterman including all PowerCLI scripts for people don´t want to do all things manually (like us) can be found here: VMware PowerCLI and Pure Storage

The complete best practice guide can be found here: Pure Storage and VMware vSphere Best Practices Guide

Of course after doing all the changes and uploading our data to Health Analyzer again all issues were detected as resolved! Basic Pure Storage multipathing complete!

Start checking your vSphere storage configuration!

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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.

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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.

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

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  • 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.

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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

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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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