Oracle’s Cloud Infrastructure has been designed in an API-first manner, which is awesome for all sorts of infrastructure automation tasks. It also implements an interesting API security model, in which all requests must be signed using a private key, associated with a public key which has already been configured in OCI (here, the developers are showing their infrastructure roots, as this echoes how SSH Auth is normally handled). The documentation of this model provides sample code in a number of languages, which is perfect if you are writing automation scripts, but is a little inflexible for ad-hoc testing. Typically I much prefer to use a rich graphical REST client, such a Postman, so that I can easily tweak my parameters and try out different types of calls before I write any code. Unfortunately while Postman is well equipped for Basic and Token based Auth, HTTP-Signature is not natively implemented, and rather than abandon Postman for a new tool, I set out to implement it using Postman’s powerful scripting capabilities. In this blog post I provide the result of this, which is a downloadable collection which provides all of the required scripts, and discuss the approach used.Continue reading “Calling OCI APIs from Postman”
Last week, I had a question about a customer wanting to migrate their issue management to Oracle Developer Cloud (https://cloud.oracle.com/en_US/developer_service). They had hundreds of issues to migrate and saw that it was a big task to re-enter all of the detail. Also, it was all in Excel. This article is about the experiences and steps that we took to import the issues from Excel. And as the title of the article eludes to, we used the APIs available.
Building a Multi-Lingual Bot on the Oracle Chatbot Platform
First things first, if you are new to building Chatbot using the Oracle Cloud Platform, here are some quick videos to get you started on the platform and its capabilities. There is also an online MOOC (Massive Open Online Course) available on how to build your first BOT using the Oracle Platform and access the Bot through Facebook Channel.
Now that we understand how to build a bot let’s turn the Bot that can recognise the input from the end user conversing in his/her own language and respond accordingly.
The Bot platform allows you to bring your own translation keys (Google / Bing) and the Bot can be configured to detect the language. The bot further converts the user input to English, intent recognition by the NLP engine kicks off, based on the dialogue flow the bot structures the response in English which is again translated back into the language in which the question was asked by the user.
Let’s see that this in action :
With all the recent exciting releases of Oracle Autonomous PaaS Services, I wanted to explore some of the client connectivity options to work against the Oracle Autonomous Data Warehouse (ADW).
In my cloud subscription I provisioned an instance of ADW which took less than two minutes from start to finish – terrific, now I am ready to leverage the functionality. If you want to know the steps to provision an ADW instance check out this blog post – https://redthunder.blog/2018/07/02/teaching-how-to-get-started-with-oracle-autonomous-data-warehouse-cloud-service/
Obviously an empty data warehouse isn’t particularly useful so one of the first things I wanted to do was to connect a SQL client to the ADW instance so that I can load some data. Initially I used Oracle SQLDeveloper to load data into my ADW instance. I had staged my Excel data files into an Oracle Cloud Object Storage container and then referenced them in my SQL code as External Tables. Carlos has already blogged the steps required for this in https://redthunder.blog/2018/07/02/teaching-how-to-get-started-with-oracle-autonomous-data-warehouse-cloud-service/ . If you follow the steps you will quickly get your ADW instance populated with your data. In fact for the demo scenario my ADW instance was now populated with some data (approx. 1 Million rows of Sales data and associated related dimensions (Product, Customers etc).
My next step (and the subject of this blog post) was to use the Oracle Instant Client in order to query the loaded data. Of course I could easily have viewed the data inside SQLDeveloper but I wanted to try some other approaches. Often in Proof of Concepts there is a need to quickly spin up a tool to create, retrieve, update and delete data. Anyone who has used the Oracle Database would be familiar with the SQL*Plus client which is included as part of the Oracle Instant Client. For those who are not familiar with Oracle Instant client, the Oracle website describes it as follows,
“Free, light-weight, and easily installed Oracle Database tools, libraries and SDKs for building and connecting applications to an Oracle Database instance. Oracle Instant Client enables applications to connect to a local or remote Oracle Database for development and production deployment. The Instant Client libraries provide the necessary network connectivity, as well as basic and high end data features, to make full use of Oracle Database. It underlies the Oracle APIs of popular languages and environments including Node.js, Python and PHP, as well as providing access for OCI, OCCI, JDBC, ODBC and Pro*C applications. Tools included in Instant Client, such as SQL*Plus and Oracle Data Pump, provide quick and convenient data access.”
I used a Vagrant-Box / VirtualBox to avoid having to install development tools such as the Oracle Instant Client directly on my laptop operating system. I found an existing vagrant box that provided me with an Oracle Linux base that also included Docker. This vagrant-box image allowed me to quickly spin up a base environment which in turn allowed me to focus on steps to run the Oracle Instant Client inside a Docker container inside the Virtual Box environment (sounds like a cheesecake recipe – lots of layers). The Dockerfile I used was based on the Oracle Instant Client forked from the official Oracle DockerImages project with some modifications for specifics around connecting to an Oracle Data Warehouse Instance. Continue reading “Connect Dockerised Instant Client to Autonomous Data Warehouse”