opvizors-performance-analyzer-3-is-certified-datacore-ready

Opvizor Inc. today announced that its Performance Analyzer 3 is certified DataCore Ready for SANsymphony ™, from the Software-Defined Storage Platform from DataCore™ Software, making them beneficial for organizations to maximize the availability and utilization of IT assets and to simplify data storage management.

“It is a great pleasure to announce the DataCore Ready Solution certification for our Performance Analyzer 3. Our customers are now able to benefit from all the added value provided by DataCore,” said Dennis Zimmer, CEO – opvizor.

Some of our SANsymphony™ integration features are:

  • Find DataCore server bottlenecks and performance issues
  • Check caching and replication efficiency in real time
  • Full insights into Latency and IOps
  • React on front-end and backend-network anomalies
  • Combine SANsymphony™ metrics with consumer (VMware vSphere, MS Hyper-V)

DataCore Ready

Performance Analyzer 3 supports real time performance analysis through the full stack, from VMware vSphere or Microsoft Hyper-V and Docker or Microsoft SQL to DataCore Storage System.  This is all done using a highly flexible Dashboard Engine. Performance Analyzer 3.0 is a game changer – the software correlates data from a variety of datacenter components, unifies the data into one layout, providing end-to-end visibility for the user.

Here you can find some of our VMware vSphere integration features:

  • Find Disk I/O bottlenecks
  • Report Used Capacity over time and plan future capacity
  • Full insights into Datastore Latency and VM Disk IOps
  • See Memory Issues (Ballooning, Swapping) and Network Issues (Packet Loss) instantly
  • Get a complete cluster usage overview across multiple Datacenter or vCenter
  • track VMware Snapshot Usage in real time including historic data

„The interesting point with Opvizor are the flexible dashboards, they give the possibility for a comprehensive analysis of a heterogeneous eco-system in the data center. It is easy to find relationships and dependencies between hypervisors (VMware, Hyper-V, etc.) and in our case Storage-IO. " Alexander Best, Director Technical Business Development, DataCore

DataCore Ready

The DataCore™ SANsymphony™ Software-Defined Storage Platform is a comprehensive and scalable storage services platform designed to maximize the performance, availability and utilization of IT assets. The software runs in the data path and has visibility to all the read and write traffic generated by applications. It can take full advantage of the Dell PowerEdge high-speed x86-64 processors, on board DRAM memory and Dell flash based SSD cards to turn around requests quickly, while automatically tiering and moving data between spinning disks, flash and across different storage platforms to optimize performance and improve application response times.

DataCore Ready

Register here for more information and how to get the latest version of Performance Analyzer

Performance Analyzer Integrations

Blog post DataCore SANsymphony™

DataCore Ready Members

About opvizor

Opvizor offers solutions that enable a deep view into your virtualized environment. The focus of all of our solutions is the recognition of current and potential problems before outages and performance bottlenecks. The company operates offices in the United States (Houston, Texas) and Austria (Vienna). Founder and CEO Dennis Zimmer is an acknowledged expert for virtualization and was awarded already 8 years in series as a VMware vExpert due to his work as a book author and blogger.

CNIL
Metrics and Logs

(formerly, Opvizor Performance Analyzer)

VMware vSphere & Cloud
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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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