Month: October 2016

vmware-cpu-co-stop-and-sql-server-performance

A very useful article from David Klee about the intricacies of virtualization CPU scheduling and its impact on the performance of the VMs. You can read the complete article here, or see some excerpts below. You’ll need access into VMware’s vCenter Server to see this metric. It’s not visible from inside the VM. At least read-only access …

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opvizor-performance-analyzer-part-16-performance-in-real-time-for-vmware-virtual-san

Hyper-converged Virtual SAN. A high-performance, cost-effective solution. Many information about Virtual SAN in general, not limited to DataCore solution on their Homepage. But back to VMware vSAN… Versatility – Works with any hypervisor, any application, any server hardware Performance – Accelerate performance for latency-sensitive applications using server RAM for high-speed cache Scalability – Integrates with external …

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opvizor-performance-analyzer-part-15-performance-in-real-time-for-virtuozzo

Here is a white paper available for BEST PRACTICES FOR PARALLELS CONTAINERS FOR LINUXUsing I/O Limits to Maximize Container Performance Introduction I/O limits were introduced in Parallels Virtuozzo Containers for Linux 4.6 with Kernel 2.6.18, and in Parallels Server Bare Metal 5 with Kernel 2.6.32 and is now available in Parallels Cloud Server 6.0. Used …

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introducing-vsphere-6-5

There is a new release of VMware vSphere 6.5, the latest version of its industry-leading virtualization platform. This new release of vSphere features a dramatically simplified experience, comprehensive built-in security, and a universal app platform for running any app.vSphere 6.5 accelerates the customer transition to digital transformation and cloud computing by addressing key challenges: 1.     …

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opvizor-performance-analyzer-part-14-performance-in-real-time-for-red-hat-enterprise-linux

There is a performance tuning guide available for Red Hat Enterprise Linux 7.Please find the complete white paper here. Abstract The Performance Tuning Guide describes how to optimize the performance of a system running Red Hat Enterprise Linux 6. It also documents performance-related upgrades in Red Hat Enterprise Linux 6. While this guide contains procedures that are …

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vmware-cloud-on-aws

Frank Denneman published a very interesting article about the strategic partnership of VMware and Amazon Web Services (AWS), a repost of content on blogs.vmware.com Please find a repost of Frank’s article: Today, VMware and Amazon Web Services (AWS) are announcing a strategic partnership providing the ability to run a full VMware Software Defined Data Center …

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opvizor-performance-analyzer-part-13-performance-in-real-time-for-apache-http-server

Here is a complete power point for your Apache performance tuning. Top 6 best practices for fine-tuning your Apache performance by Ralph Eck Keep your Apache updated with the latest releases and patches Disable Directory Listing Disable unnecessary modules & services Ensure that Apache server-info is disabled Disable Trace HTTP Request Leverage Monitis Apache Tomcat …

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opvizor-performance-analyzer-part-12-performance-in-real-time-for-microsoft-hyper-v

6 Best Practices for Physical Servers Hosting Hyper-V Roles From the Microsoft Press ebook Understanding Microsoft Virtualization Solutions: From the Desktop to the Datacenter by Mitch Tulloch. Avoid Overloading the Server Ensure High-Speed Access to Storage Install Multiple Network Interface Cards Configure Antivirus Software to Bypass Hyper-V Processes and Directories Avoid Storing System Files on …

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opvizor-performance-analyzer-part-11-performance-in-real-time-for-azure-sql

Performance best practices for SQL Server in Azure Virtual Machines, find the complete article from Microsoft Azure here incl a quick check list by Jason Roth. "This topic provides best practices for optimizing SQL Server performance in Microsoft Azure Virtual Machine. While running SQL Server in Azure Virtual Machines, we recommend that you continue using the same …

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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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