Amid the infinite sessions about AI, I could also find some on other topics. I started my journey with a session on security best practices.

Then came the keynote, where I could see a demo of an automated delivery robot shaped like a dog that can climb stairs. During the keynote, it was announced that Oracle Exadata would be available in the Zurich region starting 2026.

Among the other sessions I attended, I can spotlight one on the IAM service, where the speakers deep-dived into how to manage the service more accurately.

I also attended a session addressing the Sovereignty topic where we were explained the impact of the CLOUD act and the data protection subject.

I also went to a network focused presentation, the speaker showed us the new features of AWS Cloud WAN and how it works as a backbone network for hybrid solutions. The biggest news was that now we can connect AWS Direct Connections directly to AWS Cloud WAN without the need of a transit gateway.

They also introduced to us VPC Lattice, a fully managed application networking service that you use to connect, secure, and monitor the services and resources for your application.

Finally, I followed a session on cloud cost optimization. We were presented some dashboards that we can use to optimize our cloud costs.

That’s it for this year. Yet another summit where I’m able to learn new stuff. I hope I can go again next year and still learn new skills.

L’article AWS Summit Zurich 2025 est apparu en premier sur dbi Blog.

S3 storage is the most resilient and available service in AWS: is a trusted service for storing backups over the long term.

From a Windows Server machine, in AWS EC2 or elsewhere, the easiest and most reliable way to make a backup from SQL Server:

• Via URL, natively supported since SQL Server 2022
• Via a Storage Gateway with File Gateway, which exposes an SMB share. The Storage Gateway will be responsible for replication to S3

1- Concept

For data that must be available over a long period of time (finance, insurance, medical), less costly archiving can be envisaged as follows:

• By optimizing the type of storage class
• Reduce the volume of backups with a retention strategy

a- Backup Retention

For a customer project, we chose to implement the following strategy:

• All backups with 30 days retention (with standard storage class)
• A Full backup a month with 12 months retention (with glacier storage class)
• A Full backup a year with 15 years retention (with deep-archive storage class)

To do this, we decided to create, in a Bucket, the following 3 Prefixes:

• Daily: contains all backups (.bak, .trn…) in last 30 days
• Monthly: contains the first FULL backup of the month in the last 12 months
• Yearly: contains the first FULL backup of the year in the last 15 years

b- S3 Lifecycle Policy

To implement the retention, we did set up a lifecycle rule on each 3 prefixes.
These rules include the following parameters:

• A Transition Action: the object is converted into the default storage class for the prefix, based on the backup retention decided above. Of course, it’s more efficient to create them in the right storage class first
• A Retention Action: the object is deleted after a defined period

c- Archiving backups

While lifecycle exists natively in S3 with Lifecycle Policies, there is no native mechanism which moves S3 objects between prefixes.
Generating a backup once a month and/or a year from SQL Server to S3 is not efficient since backups are already present in Daily prefixes.
To do this, you need to set up a custom script which will archive backups from Daily to Monthly and Yearly.

This script can be scheduled, for example, by AWS Lambda or another scheduler tool.
In our context, we did choose SQL Server Agent to schedule the archiving after the backup step in a job for the following reasons:

• Execute archiving as soon as a new backup (if eligible) was generated
• Get access easily and modify it, if necessary, from the database server. Of course, the script is server and instance agnostic… but you may want to temporarily modify it on a server as a workaround

2- Implementation

a- Accessing S3

First, a IAM role must be attached to the EC2 instance to authorize the access to the S3 Bucket where backups are stored. Keep in mind this access is available at the machine level, that’s why I recommend to restrict access to read/write only.
This role is accessible, on the OS, through a metadata token as follows (IMDSv2 requirement):

[string]$token = Invoke-RestMethod -Headers @{"X-aws-ec2-metadata-token-ttl-seconds" = "21600"} -Method PUT -Uri http://169.254.169.254/latest/api/token
# This sens a PUT request to get a token valid for 6 hours

Once the token retrieved, you can securely accessed the role assigned the the EC2 instance:

$roleName = Invoke-RestMethod -Uri "http://169.254.169.254/latest/meta-data/iam/security-credentials/" -Headers @{"X-aws-ec2-metadata-token"=$token}

From there, you can get temporary security AWS credentials for this role:

$credentials = Invoke-RestMethod -Uri "http://169.254.169.254/latest/meta-data/iam/security-credentials/$roleName" -Headers @{"X-aws-ec2-metadata-token"=$token}

Then, you can set the credentials using AWS Tools PowerShell module:

Set-AWSCredential -AccessKey $credentials.AccessKeyId -SecretKey $credentials.SecretAccessKey -SessionToken $credentials.Token
# Credentials set for the current PowerShell session

b- Retrieving backups to archive

Using dbatools PowerShell module, we retrieve the first backup based on a reference date.
Here is an example when a Storage Gateway with File Gateway is used as a destination:

# $RefDate = New-Object DateTime( $Today.Year, $Today.Month, 1 ); # First backup of the month
# $RefDate = New-Object DateTime( $Today.Year, 1, 1 ); # First backup of the year

$BackupHistory = Get-DbaDBBackupHistory -SqlInstance $ConnectionString -Since $RefDate -Type Full -DeviceType Disk | Group-Object Database;

foreach ($Database in $BackupHistory){
      $Backup = ($Database.Group | Sort-Object End)[0];
      $Files = $Backup.Path;
      foreach ($File in $Files){
            # Process your copy
      }
}

c- Archiving backups

To process the copy, we must construct the key location and the key destination in S3 based on the information retrieved in msdb.
So, it mainly depends on your prefix structure in your bucket ; which must remains the same over the time.
Here is an example when the structure is RetentionPeriod\InstanceFolder\DatabaseName\FileName:

# Process copy for each file
$Leaf = Split-Path -Path $File -Leaf;

# Construct Source Key in S3
$SourceKey = "$($RefSource)/$($InstanceFolder)/$($Backup.Database)/$($Leaf)";

# Construct Destination Key in S3
$DestinationKey = "$($RefDestination)/$($InstanceFolder)/$($Backup.Database)/$($Leaf)";

# Copy the backup to the new Prefix
Copy-S3Object -BucketName $bucketName -Key $SourceKey -DestinationKey $DestinationKey -StorageClass $StorageClass -Region $Region;

CONCLUSION

In this blog, we demystified all the concepts and steps required to implement a backup strategy in AWS EC2 for SQL Server.
For other RDBMS running in EC2, the approach and code used for archiving would be very similar.

If you restrict access to Storage Gateway with File Gateway with READ/WRITE permissions and you enable COMPRESSION in SQL Server, then I recommend you read this blog I wrote:
Random permission denied when backing up SQL Server databases to AWS Storage Gateway

L’article Guidance for a SQL Server backup strategy in AWS EC2 est apparu en premier sur dbi Blog.

When SQL Server is hosted on AWS EC2 instances, you’ll need to manage the backup strategy appropriate to your business.

In order to persist and archive your SQL Server backups securely and permanently, AWS S3 is a prime target: it’s the service with the best availability and durability in AWS.

However, if you don’t have a version prior to SQL Server 2022, you can’t natively backup to S3.

In this context, you need to use an intermediary service: a Storage Gateway with File Gateway.

The Storage Gateway is a storage service that enables you to replicate (and extend) your data in the S3 Cloud. It can be deployed either on-premises or in the Cloud, making it an hybrid cloud solution.
To use it with SQL Server, you need the File Gateway type, which exposes an SMB file share; in the context of Windows Server.

Here is a simple architecture example with a SQL Server hosted on EC2:

In the S3 bucket, a classic structure is to create several prefixes (kind of folders) as follows:

• A prefix for daily backups with a short-term retention policy
• A prefix for monthly backups with a middle-term retention policy
• A prefix for yearly backups with a long-term retention policy

Of course, storage class may differ between these different prefixes to optimize cost.
In addition, for security and cost reasons, you’ll want to use an S3-level retention policy to remove backups over time (called S3 Lifecycle rules).

For added security, and to prevent backups being modified or deleted from the SMB fileshare, access can be restricted to read and write permissions only: this is what we’ve done in our context.
Moreover, to save space as much as possible, we enabled compression at SQL Server level.

This is the combination of these specifications which can, randomly, introduce the following error: Unable to open the physical file. Operating system error 5: “5(Access is denied)”.

To understand this error, let’s see how backup compression works with space allocation for the backup file.
SQL Server will first estimate the size of the compressed file (with a preallocation algorithm), but the final size may vary (can be at the end higher or lower) depending on how compressible the data is.

The above error occurs when the backup file is higher than needed, and the system tries to shrink the file to release unused space. This action requires Modify permissions, and an Access Denied will be triggered.

In our context, Modify permissions was not an option for security reasons.
As a workaround, we did enable Trace Flag 3042 which bypass preallocation algorithm. As a result, the file will grow as the backup progresses, requiring only Write permissions.

Keep in mind that increasing backup files over the time are less performant than preallocated algorithm: backup duration may increase for databases); but acceptable in our context.

L’article Random permission denied when backing up SQL Server databases to AWS Storage Gateway est apparu en premier sur dbi Blog.

YaK core Multi-Platform open source Automation Tool simplifies the deployment of Ansible playbooks through a clean UI and API. It offers an intuitive interface where users can upload playbooks, configure parameters, and deploy them seamlessly across various platforms, and all managed through a centralized inventory stored in a PostgreSQL database. With YaK Core, developers can focus on writing application code without worrying about infrastructure setup or management.

YaK consists of two parts: YaK Core, which is open source, and YaK Components, which can be installed on top. These YaK Components are platform-agnostic service packages (e.g., PostgreSQL, Oracle DB, MongoDB, Kubernetes, etc.), written in Ansible by experts. They provide essential operational features such as backup, patching, upgrades, and high availability. If you’d like to learn more about the available YaK components, feel free to contact us!

But that’s not all. YaK Core also lets you create your own YaK Components . Once created, your component becomes immediately available for deployment across all platforms supported by YaK Core.

In this blog, I’ll show you how easy it is to create your own YaK Component using Ansible, upload it to YaK Core, and deploy it across any supported platform.

YaK Demo platform provisioning

To get started with YaK Core Multi-Platform open source solution, visit https://yak4all.io and provision your own YaK demo environment (take 5 minutes to be ready).

Build your YaK Component

To build a YaK Component, you need to declare at least the following three files

1. playbooks/create_linux_users.yml
2. manifest.yml
3. yak_variables_specifications/basic_variables_specifications.yml

1. The Ansible Playbook

playbooks/create_linux_users.yml
This file is simply your Ansible playbook, nothing more. The only requirement is that the code uses variables, which will be exposed in the UI for configuration. The example playbook below will create a user and optionally grant them sudo privileges.

---
- name: Create Linux users
  hosts: linux_hosts
  become: true
  gather_facts: true

  tasks:
    - debug:
        var: user

    - name: Create users
      ansible.builtin.user:
        name: "{{ item.username }}"
        create_home: "{{ item.create_home | default(true) }}"
        state: present
      loop: "{{ user }}"

    - name: Add users to sudoers
      community.general.sudoers:
        name: "yak-sudoer-{{ item.username }}"
        user: "{{ item.username }}"
        commands: ALL
        state: present
      loop: "{{ user }}"
      when: item.is_sudoer
        
  post_tasks:
    - name: Update component state
      delegate_to: localhost
      yak.core.yak_component_state_update:
        component_state_name: 'deployed'
...

2. Manifest file

manifest.yml
This file contains the basic information about your component and specifies which playbooks can be executed.

name: linux_users

version:
  major: 1
  minor: 0
  patch: 0

sub_component_types:
  - display_label: Linux users
    name: create_linux_users
    features:
      - display_label: Create Linux users
        name: create_linux_users
        playbook_name: playbooks/create_linux_users.yml

    inventory_maps:
      - group_name: linux_hosts
        group_nicename: Linux hosts
        group_description: Host on which the users will be created
        group_min_hosts: 1
        group_max_hosts: 100
        type: host
        os_type: Linux

3. Variable specification file

yak_variables_specifications/basic_variables_specifications.yml
Now you can define and provide all the specifications for the variables you want to make configurable, with all the required settings .

- variableName: user
  niceName: Users to create
  dataType: array
  children:
    - variableName: username
      niceName: Username
      dataType: string
      mandatory: true
      defaultValue: yak
      isOneOffSetting: false
      usage: Name of the user to create

    - variableName: create_home
      niceName: Create Home directory
      dataType: boolean
      mandatory: true
      defaultValue: true
      isOneOffSetting: false
      usage: Tick the box if you want to create a Home directory for the user (/home/<username>)

    - variableName: is_sudoer
      niceName: Grant sudo privileges
      dataType: boolean
      mandatory: true
      defaultValue: true
      isOneOffSetting: false
      usage: Tick the box if you want to grant "ALL" privileges escalation to the user

That’s it! You now have all the necessary files for your first YaK Component. Next, create a ZIP package and upload it to your deployed YaK Demo environment.

To make things easier, I’ve created a ZIP file that you can upload directly. : create_linux_user.zip

Setup a Server

For this task, simply follow the documentation below up to Step 4: Deploy your server https://dbi-services.gitbook.io/yak-user-doc/introduction/yak-demo

Declare and deploy your Component

You’re now ready to declare and deploy your component!

1. Declare

YaK UI -> Components -> Declare -> Component_type : linux_users -> Save

2 Deploy

YaK UI -> Components -> Select LinuxUser -> Action -> Create Linux User -> Confirm

Conclusion

This component can now be deployed on any cloud platform or integrated on On-Premises environment using the YaK UI, and can also be deployed in parallel on up to 100 servers, as specified in your Manifest file.

With this solution, you can provide your colleagues with an intuitive and efficient way to work with Ansible playbooks, enhancing their overall experience .

For more Information about YaK see the blogs available here : https://www.dbi-services.com/blog/yak

L’article YaK Core – The Holy Grail for Deploying Ansible Code Everywhere est apparu en premier sur dbi Blog.

Context

Our HYCU setup is composed of multiple environments, on premise in our datacenter and in the cloud in our AWS accounts. We have a HYCU instance deployed on our Nutanix cluster which is the “master” instance, meaning that all the backups are created by this instance. The backups are saved in two environment, they are saved in our NAS server and a copy of each backup is also transferred to an AWS S3 bucket in one of our AWS accounts. We also have a secondary HYCU instance in AWS, this one is in “Restore mode” meaning that it can only restore instances and can not do any backup.

We created this setup with two environments and two HYCU instances to be able to restore our environment in case we lose our whole Nutanix cluster. The schema above represents the infrastructure with an example of restored instance with all the temporary resources created by HYCU during the process.

HYCU setup

In the HYCU console we have two parameters to configure so that the restore operations works.

First we have to configure the Cloud Account :

We also have to configure the HYCU R-CLOUD account:

When this is done, we can start the restore operations.

Virtual machine Spin-up

First step: select the virtual we want to restore:

Then we must select the restore point and click on “SpinUp to cloud”:

Then we select our cloud provider:

In this window, we select the information about the AWS account we want to use and give some detail on the region and availability zone. The AWS account ID is gathered from the HYCU R-CLOUD configuration.

Then we have to give some more details about the virtual machine such as the shape:

We also have to give the virtual machine a network adapter, so from the previous panel we click on “Add Network Adapter” and fill the following form:

The machine needs an internet access to communicate with R-CLOUD, it doesn’t need to have a public IP if you have a VPN and routing to Internet configured. In our case, we will give our test machine a public IP since our DR VPC does not have a running NAT gateway. Once we are done with the network setup, we click on “Add” and on “SpinUp” from the previous window.

In the Jobs tab in our console, a new restore job has started:

From here you can follow every step of the restore such as the creation of the temporary S3 bucket. To get information, click on “View report” at the top right:

During the SpinUp, HYCU creates a temporary virtual machine that will orchestrate the cloud operations such as the creation of a temporary S3 bucket to store your virtual machine backup data. The SpinUp will also create a snapshot based on the temp S3 bucket data, then an AMI based on this snapshot and finally recreate the virtual machine based on the AMI.

Here you can see the HYCU virtual machine and the temporary machine booted by the restore operation. The infrastructure schema would now look like this with all the temporary resources running:

After the SpinUp job is done, we see in the AWS console that my virtual machine is here:

Note that the temporary HYCU instance is automatically deleted as well as the S3 bucket created earlier. We noticed during our tests that one factor has a big impact on restore time: the temporary virtual machine shape. The bigger the shape, the lower the restore time. Just note that only the HYCU support can change this parameter for you so if you want faster restores you should raise them a ticket.

L’article How to: Restore a Nutanix virtual machine to AWS using HYCU R-CLOUD est apparu en premier sur dbi Blog.

Last week, I attended the AWS Summit Switzerland 2024 in Zürich with one of my colleague from the Cloud team. These kind of events are interesting to see the trends and stay informed on what’s new in AWS Cloud. There are no surprises for this year, the generative AI is still a very hot topic.

This short blog is about some key topics I found interesting to keep an eye on.

Amazon Bedrock

Training its own Large Language Model (LLM) requires a lot of data and compute resources. And there are already several public LLMs available. The goal of Amazon Bedrock is to provide access to some foundational models (like Anthropic, Meta, etc…) as a fully managed service.

It can be used for content generation and help you to build your own virtual assistant. Clariant showed an example with their new company assistant named Clarita mentioned in the keynote by Chris Hansen and with a dedicated presentation later on.

Being between your users and the model you want to query helps you to implement Guardrails to prevent leak of sensitive data or filter the result to match your internal policies. Generative AI is a big trend but security is big concern for many companies as data is a important asset of each company.

RAG helps improving results from foundational models

There are different approaches to customize foundation models and improve the results to match your context.

Prompt engineering does not really allow to use your own data and on the other side, training your own model brings a lot of complexity and require some investment. It leaves 2 options: Retrieval Augmented Generation (RAG) and Fine-tuning / pre-training on existing model.

RAG was a really huge topic, it’s a good way to use your company data without the need to fine-tune and train your own model. In a simplified view, when the user submit its prompt, an additional search is done in a database or with an API and the result of that search is added to the prompt to provide context and data. The assistant Clarita I already mentioned above is built with RAG to help Clariant provide its employees answers with company data including old research data that has been digitalized.

Vector database will play a role

This topic is heavily related to generative AI and RAG. As shown in the picture below, the idea is to go through an embedding model and represents human language as vectors. It works in more than 3 dimensions, and the “distance” between 2 points helps to see if they are part of the same “space”

New York and Paris are 2 cities and the 2 vectors are closer with each other than with Horse or Animal which belong to a different space. There were different speeches around RAG and vector database and it seems to be the critical peace for a custom virtual assistant. Even when I went to a deep dive session on Aurora to keep my database knowledge, one of the feature named “pgvector extension” brings me back to AI trend.

L’article AWS Summit Zürich 2024 est apparu en premier sur dbi Blog.

Starting with the keynote, I understood clearly that the main topic of the day would be generative AI. We were show various AI solutions created by AWS and implemented by some partners. And we were also explained the goal of some services like AWS Bedrock or the AWS Skill Guild, that I didn’t know before.

After that I attended a security topic explaining again how AWS and a partner secured the partner data together applying the AWS Well Architected Framework and mostly the security pillar.

Another session, another security topic! This one was more about the AWS services that enable us to have a secured environment. We saw a few details about AWS Network Firewall or even how to secure the flows using a Gateway Load Balancer with some third party firewalls running in ec2-instances.

After that I went to a AI oriented presentation. I was introduced to Large Language Model (LLM). I learnt their purpose, and how to chose the best language. The criteria were the task I want to achieve, the total cost or even the time needed to achieve it.

I then went to a networking session, where the speaker debunked the AWS networking. He made a resume of what networking used to be with physical devices and then showed us that networking in AWS is not so binding.

Finally, I went to another security session. Here I learnt about a service called AWS Security Lake. It is used to centralize data coming from multiple environments like AWS environments, on-premises or from SaaS providers.

L’article AWS Summit Zurich 2024 est apparu en premier sur dbi Blog.

First, go in Microsoft Entra ID (formerly Microsoft Azure AD) and select the menu “Enterprise applications”. That screen is already providing an overview of the certificate statuses for all the applications. In the screenshot below, we can see that I’m already late as the certificate already expired.

Then, you need to click on the application and select “Single sign-on” menu to get the current SAML configuration. The 3rd block about SAML Certificates shows again the status and other information like Thumbprint and Notification Email. In my Azure test environment, the email was set to the email address of the Microsoft Entra ID admin account. As I don’t have a real domain for this sandbox, I never got any reminder before the expiration. You can change the email notification and I strongly recommend to use a valid email address

Each application can have multiple signing certificates but only one is active at a certain time. It gives us some flexibility to prepare the renewal before the certificate expiration. To proceed with the renewal, just click on the Edit button in the top-right corner of the block. It will display a new menu on the right similar to the next screenshot.

Creating a new certificate is as easy as pushing the button “New Certificate”. The new Thumbprint is not displayed until you use the button Save. Before moving to the target application, you need to download the new certificate. Just click the 3 dots on the right to display the contextual menu and download the certificate. I usually take the PEM format but it’s also available in base64 or raw formats.

Once the new certificate on the IdP side is ready, we may need to import it in the target Service Provider. In this blog’s case, it will be in AWS IAM Identity Center. In the settings page, look for the Identity source parameters and click on the “Actions” menu to select “Manage authentication”. At the bottom of the page, the known certificates are displayed. In my case, there is only one and it’s expired.

Click on the button “Import certificate” and select the certificate you downloaded before from Azure. AWS will then display the new certificate alongside the old one. At this moment, both certificate could be used by Azure. In an ideal case, you would add this new certificate before the old one expires and there would not be any downtime.

Only one certificate can be active at a time in Azure. It’s now time to go back in the Enterprise application in Azure in the management certificate page. Click on the menu and make the new certificate active.

I recommend to perform some cleanup and remove the expired certificate from both sides afterward.

In this blog, we fixed the access issue due to an expired certificate. As it’s my lab environment, it impacted only myself. But, more important, we know it’s possible to have multiple certificate in both sides. So I strongly recommend to generate the new certificate few days or 2 weeks before the expiration to avoid any interruption for your users.

L’article Renew expired certificate for your SAML SSO application in Azure est apparu en premier sur dbi Blog.

This week I could go to the AWS re:Invent re:Cap in Geneva. This event, organized by AWS, gives a resume of the biggest announcements made in the famous re:Invent in Las Vegas.

The topics addressed during this event covered various cloud technologies where AWS is investing resources to develop. We had a recap of the news regarding Generative AI, Data and Analytics, App Modernization and Developer Experience or event Management and Governance.

Generative AI

In the generative AI part, we were mainly introduced to Amazon Q, a chat bot made in AWS. As of the features we saw that Q can integrate with more than 40 data sources. It also uses multiple sources for user management like AWS SSO or Entra ID. The main purpose is to answer user queries based on their rights to access documents, so the answers are filtered so users only see what they are allowed to.

Database and Analytics

For the Database and Analytics topic we had an introduction to zero ETL. This topic shows AWS ambitions to reduce the need of pipelines. They want to create trust relationships between databases and redshift to get rid of the pipelines.

Another point presented in this topic was translator to generate SQL query based on the human language. This feature is used by Redshift and will enable people to create SQL queries based on natural phrases. It also uses Amazon Q as a base.

Applications and DevExp

During this session, we mainly learned about CodeCatalyst, which is a unified software development service. It allows us to do a full project management in one tool, with issues as Gitlab/Github. A big point here was the role of Amazon Q. We can directly assign issues to this IA tool and it will do the job to resolve it. Then we just have to commit the code, merge it and that’s it.

We also got an introduction to CodeWhisper, a tool that helps developer to create their code. This service is now compatible with IaC languages, like Terraform and it can be integrated directly into some IDEs like Visual Studio.

Management and Governance

Last but not least, we had an introduction to the newest features in terms of management and governance. In terms of security, we learned that AWS inspector can now be used with CI/CD plugins or that GuardDuty can now look at runtime events in containers.

We also had a talk about the frugal architect way int eh cloud, which are pillars created by Dr Vogel to help people have more sustainable and more performant cloud services by optimizing the costs. We were also introduce to the newest monitoring features for example a new Application panel that shows us all the costs for a specific application deployed in AWS.

Most of the features we saw were only on preview or available in some specific regions (mostly US regions). No doubt that all those features will soon be available globally.

L’article An AWS journey in Geneva est apparu en premier sur dbi Blog.

After a welcome coffee to meet each other, Pascal Zanette shortly introduced the event and the agenda of the day.

Our CTO Hervé Schweitzer presented then YaK, developed by dbi services.
The idea was born 2 years ago, to find a solution to deploy Oracle instances on several Cloud providers (Oracle, Microsoft Azure, AWS) and On-Premises:
– in the same heterogeneous way
– avoiding constraints of each Cloud providers solution
– automated through Ansible.
YaK is made of 2 parts:
– YaK Core – as an Open Source collection (for the central inventory and instances deployment)
– YaK Components – based on a subscription (for database deployment and with dbi services best practices integration).
Hervé showed how YaK works more in details through a demo, that you can play again here.
YaK is already available for Oracle and PostgreSQL. YaK for SQL Server, MariaDB, Kubernetes, WebLogic, MongoDB and Alfresco is under development and will come soon, so stay tuned!

Marc Wagner presented how to migrate from On-Premises to Oracle OCI using Zero Downtime Migration tool (ZDM).
Marc talked about advantages to go to the Cloud (such as scalability and flexibility, no dedicated hardware, less responsibility), but also alerted the audience about things to think about (such as performances and latency, costs monitoring, lock-in risk, sensitive data). Once we decided to make this change, what about downtime to migrate to the Cloud? That’s why ZDM is interesting: it’s high available (applying MAA Best Practices), it offers a very short downtime and a minimal impact on production systems and reduces human errors. ZDM allows to migrate to Oracle OCI but also to On-Premises Exadata, Exadata Cloud@Customer (ExaCC), Autonomous Database, etc…
And finally Marc presented through a live demo how to use ZDM with an Offline Logical Migration workflow to migrate from On-Premises to ADB (you can find a summary here).

As a last session of the event, Marc Keller, with Frank Zeindler remotely, presented Cloud migration made easier and safer with data validation. Marc explained why an extra validation after a data migration is helpful and how the OMrun framework can compare data and orchestrate various processes for this purpose. Some OMrun use cases were then explored:
– Quality assurance for reporting
– Data integrity monitoring for system changeover and production
– Data crawling and data cleansing
– Data masking
– Data quality assurance during migration to the Cloud.

The event is over. After a nice lunch break with colleagues, customers and attendees, we can come back home keeping in mind the magic triple jump to go to the Cloud (as Marc mentioned during his session):
– dbi services YaK
– Oracle ZDM
– OMrun.

Last thing: don’t forget that another “Oracle Cloud Infrastructure: everything for an efficient migration” event will take place on May 23 in Basel.
And some other dbi services events will be organized during the year about DevOps, Cloud, Data and much more. So again, stay tuned!

By Elisa Usai

L’article An overview of “Oracle Cloud Infrastructure: everything for an efficient migration” event by dbi services est apparu en premier sur dbi Blog.